# mcp-knowledge MCP server

100+ MCP tools for AI agents: content metadata, trade intelligence, business-expertise analysis.

## Links
- Registry page: https://www.getdrio.com/mcp/io-github-getgapup-mcp-knowledge
- Repository: https://github.com/getgapup/gapup-mcp

## Install
- Endpoint: https://mcp.gapup.io
- Auth: Not captured

## Setup notes
- Remote endpoint: https://mcp.gapup.io

## Tools
- content_catalog - Browse the Gapup gold-standard content catalogue — video games, films, TV series and music. Returns franchises with their works (title, release year). When to use this tool: an agent needs structured, audited metadata for a cultural franchise, wants to resolve a title to a canonical entity, or browses a domain's catalogue before requesting enrichment. Inputs: a content domain and an optional case-insensitive name filter. Each franchise id can be passed to content_enrichment for its fine-grained tag profile. Endpoint: https://mcp.gapup.io
- content_enrichment - Return the enriched tag profile of a content entity — the Gapup moat. Each tag carries a facet (genre, theme, play-mode, perspective…), a confidence score, a corroboration score and its full provenance (which sources corroborated it, when). The response also carries an entity-level provenance block (average confidence, data freshness). When to use this tool: an agent has a franchise or work id (from content_catalog) and needs a fine-grained, machine-readable, verifiable characterisation for matching, recommendation, contextual targeting or analysis. Inputs: an entity id and its type. Endpoint: https://mcp.gapup.io
- content_discovery - Discover content franchises within a domain. Two modes: pass `tag` for a precise taxonomy match (every game tagged 'co-op'), or pass `query` for free-text SEMANTIC search powered by pgvector embeddings — finding franchises by meaning ('dark atmospheric games about isolation') even when no literal tag matches. Results are verifiable: tag mode carries tag confidence/corroboration, semantic mode carries a similarity score; both carry entity freshness. When to use: an agent wants a domain-scoped shortlist by tag or by intent. Inputs: a domain plus either a tag or a free-text query. Endpoint: https://mcp.gapup.io
- content_similar - Find content entities similar to a given one. For embedded franchises this uses SEMANTIC vector similarity (pgvector) over the enrichment profile — surfacing entities that feel alike even when their tags differ literally. Falls back to shared enrichment-tag overlap for works or non-embedded entities. Each result carries a similarity score and its entity-level freshness/confidence (verifiable, sourced). When to use this tool: an agent wants recommendations or lookalikes for a franchise or work. Input: an entity_id and its type. Endpoint: https://mcp.gapup.io
- content_taxonomy - Return the enrichment taxonomy of a content domain — every tag grouped by facet (genre, theme, mood, play-mode…). When to use this tool: an agent needs the controlled vocabulary to filter, classify or query content. Input: a domain. Endpoint: https://mcp.gapup.io
- content_audience_profile - Return the audience targeting profile of a content entity — its enrichment tags reframed as audience facets with confidence, corroboration and full provenance (verifiable, sourced). The response also carries an entity-level provenance block (average confidence, data freshness). When to use this tool: an ad-tech or marketing agent needs a machine-readable, verifiable audience descriptor for a franchise or work. Input: an entity_id and its type. Endpoint: https://mcp.gapup.io
- content_provenance - Audit the full data provenance of a content entity — all its enrichment tags with their extraction source, corroboration score, source list and last verification date, plus an entity-level freshness summary. Use this tool before citing or relying on enriched content data in a high-stakes context (ad targeting, editorial, analysis). Inputs: entity_id (required) and entity_type (franchise or work). Endpoint: https://mcp.gapup.io
- content_compare - Compare the tag profiles of two content entities (franchises or works) and measure how similar they are. Returns a Jaccard similarity score, the list of shared tags, the tags unique to each entity, and a breakdown of shared tags by facet. When to use this tool: an agent needs to compare two franchises or works (e.g. 'how similar are Dark Souls and Elden Ring?', 'what do Street Fighter and Mortal Kombat have in common?', 'on which axes do these two games differ?'), find positioning overlap, identify cross-sell opportunities, or answer 'if you liked X you might like Y' questions backed by data. Works for any domain (video-games, music, film, tv). Endpoint: https://mcp.gapup.io
- content_ranking - Return the TOP-ranked content entities in a category, by a chosen criterion — the direct answer to superlative / decision queries: 'best video games', 'top RPGs', 'cheapest games', 'best value RPGs', 'best FPS playable right now', 'most popular music artists'. Criteria: critic_score, popularity, price, value (critic score per unit price). `direction` flips it (asc = cheapest/lowest first). `available_only` restricts to entities currently buyable. Sliceable by genre and release-year window; every result carries its score, price and source. When to use: an agent must produce a ranked shortlist to support a recommendation, a purchase or a 'what is the best X' decision. Endpoint: https://mcp.gapup.io
- ftg_market_gap - Return the import/production market-gap opportunities for a country — commodities where local demand outpaces local supply. Each opportunity carries the gap value (USD/year), the gap volume (tonnes/year), a 0-100 opportunity score and the potential margin. When to use this tool: an agent needs to know what a country structurally under-produces or over-imports, for trade sourcing, import/export or local-production investment decisions. Input: a country (ISO-2 code or name). Endpoint: https://mcp.gapup.io
- ftg_production_methods - Return the production methods for a commodity — each with a description, ordered process steps, pros/cons and a popularity rank. Methods are commodity-canonical: one curated set per commodity, reusable across every country. When to use this tool: an agent evaluates HOW a commodity is produced or processed, compares techniques, or builds a production plan. Input: a commodity slug or name. Endpoint: https://mcp.gapup.io
- ftg_sourcing_buyers - Return verified local buyers in a country — companies sourcing a given commodity, with buyer type, city, website, annual volume range and certification requirements. When to use this tool: an agent builds a sourcing or export shortlist, or needs real B2B demand contacts in a market. Input: a country and an optional commodity filter. Endpoint: https://mcp.gapup.io
- ftg_opportunity_scout - Rank the best countries for a given commodity — where the market gap, opportunity score and potential margin are highest. Cross-country scouting. When to use this tool: an agent has a commodity and needs to know WHERE to sell, export to or set up local production. Input: a commodity name. Endpoint: https://mcp.gapup.io
- ftg_business_plan - Return the business plan for a market-gap opportunity — direct-trade or local-production, with CAPEX, OPEX, ROI, payback period, automation level and the full plan. Cache-first: returns the stored plan when available, otherwise reports that generation is required (the FTG platform produces plans on demand). When to use this tool: an agent has an opportunity_id (from ftg_market_gap) and needs the investable plan. Input: an opportunity_id. Endpoint: https://mcp.gapup.io
- ftg_production_economics - Return production cost benchmarks (CAPEX/OPEX per unit, value ranges, scenarios, quality tiers) and agronomic yields (t/ha, cycles per year) for a commodity. When to use this tool: an agent sizes the economics of producing a commodity. Input: a commodity, with an optional country. Endpoint: https://mcp.gapup.io
- ftg_investor_directory - Return investors from the FTG directory — VC, PE and impact funds with type, firm, website, ticket-size range, sectors and stages of interest. When to use this tool: an agent builds a fundraising shortlist. Input: optional country and limit. Endpoint: https://mcp.gapup.io
- ftg_country_regulations - Return import, trade and production regulations for a country — category, title, summary and source. When to use this tool: an agent checks regulatory or compliance requirements before trading or producing in a market. Input: a country, with an optional category. Endpoint: https://mcp.gapup.io
- ftg_business_ideas - Return vetted, automation-scored business ideas from the FTG idea bank — each with an autonomy score, monetization model and conservative/median/optimistic MRR projections. When to use this tool: an agent or founder wants ranked, buildable business ideas. Input: optional category and limit. Endpoint: https://mcp.gapup.io
- ftg_country_study - Return the in-depth FTG country study — multi-part structured analysis of a country's trade and production landscape. When to use this tool: an agent needs deep country context before a sourcing, export or investment decision. Input: a country. Endpoint: https://mcp.gapup.io
- ftg_seller_catalog - Return seller catalogues registered on FTG — exporters and producers with their commodity, monthly capacity, certifications and target export markets. When to use this tool: an agent builds a supplier or sourcing shortlist. Input: optional seller country and commodity. Endpoint: https://mcp.gapup.io
- competitor_intel - LLM-narrated competitive-intelligence BRIEFING — for human consumption (board meeting, pitch prep). Pair tool: `competitive_deep_dive` for raw structured multi-source data (agent-shaped JSON). Returns: recent competitor moves with severity (critical/high/medium/low), prioritised signals, pricing-radar comparison, 3-6 quantified recommendations (impact in € or %, 7/30/90/180-day horizons), and an 8-12 slide presenter script. Use when the buyer wants a narrative briefing or a deck. Inputs: your company (name + one-paragraph pitch) + 1-10 competitors. Delivered by Manue, AI CMO of the Gapup portfolio. Endpoint: https://mcp.gapup.io
- trend_watcher - Monitor emerging trends, regulatory shifts and adoption signals for a given market sector. Returns 5-12 trend cards, each with a momentum score (rising/stable/declining), a 3-month and 12-month outlook, opportunity windows, and recommended actions. When to use this tool: the user asks what is heating up in a market, wants to time a product roadmap or content calendar, or needs an early read on a sector. Inputs: a sector to monitor and 3-8 keywords defining the watch perimeter. Delivered by Manue, the AI CMO of the Gapup portfolio. Endpoint: https://mcp.gapup.io
- partnership_synergies - Identify and rank strategic partnership opportunities for a company. Returns 5-12 high-fit partnership targets, each scored on revenue lift, time-to-impact, integration complexity and regulatory risk, with a rationale and a recommended first-step outreach playbook. When to use this tool: the user wants business-development or alliance ideas, or M&A target screening before deeper due diligence. Inputs: the user's own company and the strategic axis to unlock through partnership (e.g. enter a new market via distribution, add AI infrastructure without rebuilding). Delivered by Antoine, the AI CSO of the Gapup portfolio. Endpoint: https://mcp.gapup.io
- pitch_deck_storyline - Build a complete investor pitch-deck storyline for a company. Returns an 8-20 slide narrative tailored to the target audience (seed-vc / series-a-vc / growth-vc / strategic / bank / grant) — each slide carrying a title, key points, a speaker note and a visual hint — plus a Q&A bank of 10-15 likely board questions and traps to avoid. Output is deck JSON ready to export to Google Slides, Notion or Pitch.com. When to use this tool: the user is preparing a fundraise, a board meeting, or an investor presentation. Inputs: the company profile and the target audience type. Delivered by Sarah, the AI Fundraising lead of the Gapup portfolio. Endpoint: https://mcp.gapup.io
- carbon_footprint_calculator - Calculate a company's greenhouse-gas footprint under the GHG Protocol (Scope 1 + 2 + 3, in tCO2eq, tier-2 accuracy ±20%). Returns the emissions breakdown, hotspot identification, 5-8 reduction levers each with capex and payback, an SBTi-aligned reduction trajectory over 5-25 years, the 15 Scope-3 categories in detail, and CSRD/ESRS reporting readiness. When to use this tool: the user needs a carbon assessment for CSRD compliance pre-audit, green-finance access, or supplier ESG scorecards. Inputs: the company profile and its activity data. Delivered by Émilie, the AI Sustainability lead of the Gapup portfolio. Endpoint: https://mcp.gapup.io
- market_research_brief - Generate a structured, sourced market research brief on any market, sector or industry. Returns a machine-readable note with six sections: an executive overview, a market-size estimate (with assumptions and sources — no invented figures), key players, demand & technology trends, risk factors, and a traceable source list. When to use this tool: an agent needs to assess a new market, validate a business opportunity, prepare a pitch, or benchmark a sector before a strategic decision. Data is assembled live from keyless public sources: Wikipedia (sector context), World Bank (macro GDP/population for market sizing), REST Countries (geo context). Fields that cannot be sourced are marked 'unavailable' rather than estimated. Inputs: topic (required), geo and sector (optional refinements). Endpoint: https://mcp.gapup.io
- competitive_deep_dive - Gold-standard competitive deep dive — STRUCTURED multi-source data (no LLM narrative). Pair tool: `competitor_intel` for LLM-narrated board briefing + slide script. Aggregates Wikipedia, Yahoo Finance, SEC EDGAR, Wayback Machine, DuckDuckGo, HackerNews, domain scraping — all keyless. Returns agent-shaped JSON: KPIs (funding, employees, revenue, market cap), P0/P1/P2 competitive signals, pricing radar, competitor comparison matrix, Wayback timeline, positioning (sector/industry/icp_hypothesis/moat_signals), quality score. Every field is sourced or marked unavailable — no hallucinated figures. SLA: p50 ~25s, p95 ~30s · score 80+ on listed targets (US/EU/foreign) · score ~40 on private companies (no EDGAR/Yahoo data). Use sync for batch agents (≤30s tolerance). Use `competitive_deep_dive_async` + `competitive_deep_dive_result(job_id)` for conversational agents. Inputs: company name or domain (required), optional competitor list (≤5), optional depth (easy/medium/hard). Endpoint: https://mcp.gapup.io
- competitive_deep_dive_async - Async variant of competitive_deep_dive. Returns immediately (<200ms) with a job_id. The research runs in the background (p50≈25s, p95≈30s for depth=medium). Poll the result with competitive_deep_dive_result(job_id) after the eta_seconds hint. Use this instead of competitive_deep_dive when the agent cannot wait >15s for a response. Inputs: same as competitive_deep_dive — company (required), competitors (optional list, max 5), depth (easy/medium/hard, default medium). Async tool — register a webhook via `webhooks_manage(register, url, [job.completed])` to receive callbacks instead of polling. Faster + lighter. Endpoint: https://mcp.gapup.io
- competitive_deep_dive_result - Poll the result of a competitive_deep_dive_async job. Returns status=pending while running, status=completed with the full report once done, status=failed on error, or status=not_found if the job_id is unknown or expired (TTL 24h). Call this after the eta_seconds hint returned by competitive_deep_dive_async. Endpoint: https://mcp.gapup.io
- kyc_screener_batch - Async batch variant of kyc_screener. Accepts 1-100 names and returns immediately (<300ms) with a job_id. The screening runs in the background (up to 10 parallel KYC calls). Poll the result with kyc_screener_batch_result(job_id) after the eta_seconds hint. Each entry can specify name, type (person/company/any), and an optional birthdate hint. Use for bulk client onboarding, UBO list screening, or periodic AML refresh batches. Async tool — register a webhook via `webhooks_manage(register, url, [job.completed])` to receive callbacks instead of polling. Faster + lighter. Endpoint: https://mcp.gapup.io
- kyc_screener_batch_result - Poll the result of a kyc_screener_batch job. Returns status=pending while running, status=completed with the full array of KYC results once done, status=failed on error, or status=not_found if the job_id is unknown or expired (TTL 24h). Call this after the eta_seconds hint returned by kyc_screener_batch. Endpoint: https://mcp.gapup.io
- ai_governance_full_report_async - Audit EU AI Act complet (Règlement UE 2024/1689) — implémentation native audit-grade. Classifie le système IA selon les 4 tiers de risque (unacceptable/high_risk/limited_risk/minimal_risk/gpai) sur la base de l'Annexe III et de l'Article 5. Produit : (1) classification tier + justification + articles applicables, (2) checklist conformité Articles 9-15 + 50 + 53-55, (3) gaps documentation Annexe IV, (4) mapping ISO 42001, (5) deadlines EU AI Act 2025-2029, (6) estimation coût et effort, (7) top 10 recommandations P0/P1/P2. Retourne immédiatement (<300ms) un job_id. Poller avec ai_governance_full_report_result(job_id) après eta_seconds (~90s). Cache 7 jours pour inputs identiques. Async tool — register a webhook via `webhooks_manage(register, url, [job.completed])` to receive callbacks instead of polling. Faster + lighter. DISCLAIMER : non substitutif à un avis juridique professionnel. Endpoint: https://mcp.gapup.io
- ai_governance_full_report_result - Poll the result of an ai_governance_full_report_async job. Returns status=pending while running, status=completed with the full EU AI Act governance audit report once done (risk_tier, compliance checklist Articles 9-15/50/53-55, Annex IV documentation gaps, ISO 42001 alignment, deadlines 2025-2029, cost estimate, top-10 recommendations P0/P1/P2, compliance_score), status=failed on error, or status=not_found if the job_id is unknown or expired (TTL 24h). Call this after the eta_seconds hint returned by ai_governance_full_report_async (~90s). Endpoint: https://mcp.gapup.io
- abm_architect - Designs Account-Based Marketing (ABM) architectures for B2B companies. Call it when an agent needs to create tiered ABM strategies (e.g., 20 named accounts) with personalized playbooks, content plans, and budget allocations. Returns a structured ABM architecture including tiered account lists, playbook templates, multi-channel sequences, KPIs (pipeline, conversion, NRR), and sales alignment recommendations. Requires company/product details, target accounts with industries/revenues/stages, and key contacts. Endpoint: https://mcp.gapup.io
- account_expansion_mapper - Maps expansion opportunities for a portfolio of strategic accounts to hit NRR targets. Call when an agent needs to identify high-value upsell/cross-sell plays (e.g., seat expansion, module adoption, or new product bundles) for enterprise accounts with usage data and renewal timelines. Returns a ranked list of expansion plays with ARR impact, ICE scores, and projected NRR uplift. Requires input: company portfolio (ARR, NRR targets), account-level data (current seats, modules adopted, contract dates, usage scores, and known triggers). Endpoint: https://mcp.gapup.io
- action_plan_esg - Generates a 36-month ESG action plan with quantified actions (budget €, ROI, monthly calendar), KPIs, ESG score projections, and risk assessments. Call when an agent needs a structured, executable ESG roadmap for a company with current ESG scores and ambitions. Returns a detailed plan including 19+ actions, €550k budget allocation, 18 KPIs, and target labels (e.g., EcoVadis Gold). Requires company profile (name, sector, FTE, revenue, country), current ESG scores, and ESG ambitions per pillar. Endpoint: https://mcp.gapup.io
- ai_governance_pilot - Generates an AI governance audit report for high-risk AI systems under EU AI Act (Annex III §4), ISO 42001, NIST AI RMF, and GDPR Article 22. Agents should call this when assessing compliance for AI use cases in HR (e.g., CV scoring) before the 2026-08-02 EU AI Act deadline. Returns a structured report with KPIs (e.g., sanction exposure, high-risk classification, remediation timeline, budget) and remediation priorities. Requires company details (name, sector, FTE, revenue, jurisdictions) and AI use case specifics (name, description, data types, processing context). Endpoint: https://mcp.gapup.io
- anti_demissions_hr - Identifies employees at risk of leaving by analyzing internal HR data and external signals (Glassdoor, LinkedIn, Levels.fyi) to predict turnover. Call this when retention risk is elevated—e.g., after layoffs, leadership changes, or declining eNPS. Returns a structured report with at-risk employee count, financial exposure, estimated resignation timeline, ROI of retention actions, and a global retention risk score. Requires company profile, HR metrics (eNPS, engagement), and external signal data. Endpoint: https://mcp.gapup.io
- audit_pre_flight - Runs a pre-audit readiness check for statutory audits by analyzing financial data, known issues, and audit scope. Call it when preparing for an upcoming statutory audit to identify critical findings and missing documentation. Returns a readiness score, categorized findings (critical/high/medium), a prioritized action list, and a document checklist with availability status. Requires company details, audit parameters, financials, and any known accounting issues as input. Endpoint: https://mcp.gapup.io
- battle_cards_live - Generates a live battle card comparing your offer against a competitor in a specific deal context. Call it when preparing for a competitive sales engagement to arm your team with objections, kill phrases, disqualifying questions, and pricing traps. Returns a structured battle card with KPIs (win rate delta, objections covered, pricing edge) and actionable talking points. Requires competitor details, deal context (sector, size, persona), your offer description, and any known competitor weaknesses. Endpoint: https://mcp.gapup.io
- battle_plan - Generates a tactical 12-week marketing battle plan to hit ARR/pipeline targets. Call when the CMO needs a concrete execution roadmap with prioritized channels, weekly sprints, budget allocation, and KPIs. Returns a structured plan including target pipeline, MQLs, budget split per channel, and mitigation for blockers. Requires company name, ARR/current target, quarter, team size, budget, primary objective, top channels, ICP description, and current blockers. Endpoint: https://mcp.gapup.io
- bp_narratif - Generates a VC-grade business plan narrative for early-stage SaaS/fintech companies by grounding projections in public comparables (filings, press, Crunchbase, BPI Aides). Call it when an agent needs a bankable, investor-ready document with KPIs, valuation benchmarks, and a 4-month fundraising timeline. Returns a structured JSON with executive summary, KPIs (round size, valuation, volume, runway, dilution), and hints linking to sources. Requires company details (name, pitch, stage, country), fundraising target (amount, investor type, timeline), and key metrics (volume, growth, users). Endpoint: https://mcp.gapup.io
- brand_builder - Builds a full brand identity from founder story, vision, and target personas. Call this when an agent needs a cohesive brand book including voice profile, taglines, manifesto, elevator pitch, do/don't guidelines, and channel-specific examples. Returns a structured brand book with KPIs (e.g., brand consistency score, pricing power gain) and an executive summary. Requires founder story, vision, and target personas as input. Endpoint: https://mcp.gapup.io
- cap_table_strategist - Models and simulates cap table dilution across multiple funding rounds, secondary sales, and equity refreshes. Call it when a startup needs to forecast founder ownership, ESOP impact, or investor dilution under different funding scenarios. Returns a structured report with KPIs (e.g., founder ownership %, capital raised, secondary eligibility) and risk registers. Requires current cap table data, funding round plans, and secondary transaction details. Endpoint: https://mcp.gapup.io
- capacity_planning - Calculates headcount growth and hiring plans to meet ARR targets. Call when scaling revenue requires staffing adjustments within a defined timeframe. Returns a detailed capacity plan including FTE targets per department, hiring budgets, ARR-per-employee metrics, and critical roles with timelines. Requires current team structure, financial targets (ARR, burn rate), and department-level productivity data. Endpoint: https://mcp.gapup.io
- capital_strategy - Generates a capital strategy for scaling SaaS startups by modeling instrument mixes (equity, debt, grants), dilution, and WACC across funding rounds. Call when an agent needs a structured financing roadmap for a growth-stage company (Seed to Series C) with clear milestones and KPIs. Returns a JSON report with recommended scenarios, non-dilutive capital available, founder dilution, blended WACC, and runway projections. Requires company stage, growth plan (ARR targets, headcount), and key milestones. Endpoint: https://mcp.gapup.io
- carbon_roadmap - Generates a science-aligned carbon decarbonation roadmap for a company’s Scope 1/2/3 emissions per GHG Protocol and ADEME Bilan Carbone. Call when an agent needs quantified decarbonation levers, capex requirements, and SBTi-aligned targets for a defined perimeter. Returns a structured report with baseline emissions, reduction trajectories to 2030/2050, capex needs, hotspot analysis, and finance options. Requires company profile, operational perimeter, and emission source data. Endpoint: https://mcp.gapup.io
- champion_mapping - Maps the buying committee for a B2B deal to identify the champion, blockers, missing roles, and a multi-touch engagement plan. Call when a deal is in active evaluation (e.g., Proof of Concept) and you need a concrete go-to-market strategy. Returns a structured report with recommended champion, blockers, missing contacts, and an 8-week engagement plan. Requires deal context (company, sector, deal size, stage) and known contacts with titles, departments, and engagement levels. Endpoint: https://mcp.gapup.io
- churn_defender - Predicts B2B SaaS churn risk 60-90 days before contract renewal, scoring accounts on usage decline, NPS, escalations, and payment issues. Agents should call this when prioritizing retention efforts for high-value accounts nearing renewal. Returns a ranked list of at-risk accounts with ARR at risk, projected churn rate, and 3 tailored save-plays per account (e.g., contract renegotiation, feature adoption nudges, payment plan adjustments). Requires company financials, account-level usage metrics, contract renewal dates, and CSM notes. Endpoint: https://mcp.gapup.io
- comp_plan_architect - Designs a commissioning plan for commercial teams by benchmarking salaries, structuring OTE packages, and validating quota coverage. Call it when defining compensation frameworks for new sales hires or restructuring existing roles. Returns a structured plan with OTE breakdowns, quota targets, budget impact, and implementation roadmap. Requires company sector/stage, sales team roles/headcounts, and current compensation data. Endpoint: https://mcp.gapup.io
- content_engine - Generates a data-driven editorial plan for a brand’s content cluster, grounded in SEO benchmarks (Ahrefs/SEMrush volumes, Google Trends, competitor SERPs). Call it when an agent needs a 6-month content strategy with KPIs (traffic, MQLs, cost, ranking timelines) for a specific topic, audience, and geography. Returns a JSON report with KPIs, executive summary, and article-level recommendations. Requires brand details (name, voice, audience), cluster topic/intent/geography, timeframe, and max articles per month. Endpoint: https://mcp.gapup.io
- contract_risk_scanner - Scans SaaS or MSA contracts for buyer-side risks under French/EMEA law. Call when reviewing a high-value cloud subscription agreement (e.g., Salesforce, €480k/year) before signing. Returns a risk report with KPIs (critical severity count, financial exposure range, renegotiation list) and an executive summary highlighting clauses to amend. Requires contract text and context (our role, counterparty, deal size). Endpoint: https://mcp.gapup.io
- cross_sell_reco - Generates cross-sell product recommendations for an existing customer account by analyzing company profile, current products, and usage signals. Call this when an agent needs to identify expansion opportunities (e.g., new products or bundles) for an account with low NRR or identified growth signals. Returns a structured list of recommended products with fit scores, ARR potential, timing justification, and objection handling arguments. Requires the account's company details, current products, usage signals, and size as input. Endpoint: https://mcp.gapup.io
- customer_marketing - Analyzes a B2B customer base to identify high-potential ambassadors and generate a client marketing program. Call when the agent needs to prioritize case studies, testimonials, referrals, or ambassador programs based on customer NPS, usage, and ARR. Returns a structured plan with identified ambassadors (tiered by readiness), KPIs (e.g., advocacy score, projected referral pipeline), and actionable content templates. Requires company/product details, goals, budget, target use cases, and customer data (NPS, ARR, usage metrics). Endpoint: https://mcp.gapup.io
- customer_voice_synth - Synthesizes customer feedback (reviews, NPS verbatims, support tickets, churn surveys) into actionable personas, pain points, and messaging recommendations. Call when you need to extract strategic insights from qualitative customer data to refine positioning or product strategy. Returns a structured report with 3-5 personas, top 5 pain/gain themes per persona, and 3-5 messaging adjustments, including NPS benchmarks and segmentation analysis. Requires company context, product details, and raw customer feedback data sources with volume descriptors. Endpoint: https://mcp.gapup.io
- cyber_risk_auditor - Performs a structured cyber risk audit for midmarket B2B companies, particularly in regulated sectors like FinTech. Agents should call it when evaluating security posture, preparing for compliance audits (SOC2, ISO 27001), or negotiating cyber insurance premiums. Returns a scored audit report with KPIs (global score, critical/high findings, quick wins, insurance savings, SOC2 timeline) and a 90-day roadmap. Requires company profile (name, sector, data types), tech stack (cloud providers, apps, identity management), and current security posture (SOC, pen tests, certifications). Endpoint: https://mcp.gapup.io
- deal_coach - Analyzes enterprise deals using the MEDDIC framework to diagnose gaps, recommend escalation plays, and generate prioritized next actions. Call it when a deal is stuck in negotiation (>30 days) or shows MEDDIC score gaps (<70/100). Returns a CRO-grade report with MEDDIC scoring, KPIs, escalation plays, and 10-15 actionable next steps with owners. Requires deal context (account, amount, stage, days in stage) and buying committee roles. Endpoint: https://mcp.gapup.io
- deal_structurer - Generates and compares 5+ deal structures (e.g., revenue-share, JV, white-label) for B2B partnerships, scoring them on value capture, risks, and feasibility. Call when an agent needs a concrete term sheet, negotiation script, and KPIs for a specific deal scenario. Returns a structured output including recommended structure, ARR projections, time-to-close, and dilution impact. Requires company profiles, deal objective, estimated value, and constraints as input. Endpoint: https://mcp.gapup.io
- discovery_prep - Prepares a structured discovery brief for a sales meeting by analyzing the prospect’s company, contact profile, and industry signals. Agents should call this when qualifying a new enterprise opportunity to generate actionable insights before outreach. Returns a 1-page brief including detected buying signals, pain hypotheses, competitor context, and tailored opening strategies. Requires the prospect’s company details, contact information, target offer, and meeting objective as input. Endpoint: https://mcp.gapup.io
- diversity_inclusion_metrics - Computes and benchmarks diversity & inclusion (D&I) metrics for a company, including gender representation, pay equity, nationality diversity, and ERG coverage. Call it when an agent needs to assess current D&I performance, set 2030 targets, or validate CSRD/ESRS S1 compliance. Returns a structured report with KPIs (e.g., pay equity gap, management gender % targets), executive summary, and actionable recommendations. Requires company demographics, current-state metrics (e.g., gender split, pay gaps), and known challenges as input. Endpoint: https://mcp.gapup.io
- earnings_reviewer - Analyzes earnings call transcripts, 10-Q filings, and guidance updates to generate investor-facing analyst notes. Call when an agent needs to evaluate a public company's financial performance for a specific quarter, producing a structured report with KPI deltas, consensus beats/raises, and margin paths. Returns a JSON object with generated timestamp, case label, and an array of KPIs (value, delta, hint, color). Requires company details (name, ticker, sector, exchange), quarter label/report date, and transcript excerpt or full transcript. Endpoint: https://mcp.gapup.io
- enps_auto - Generates an automated eNPS pulse program for CHROs, including segmentation analysis, risk identification, and targeted corrective plays. Call when a company needs a structured monthly eNPS tracking solution with actionable insights. Returns a JSON report with baseline/current eNPS, target KPIs, at-risk segments, and prioritized corrective actions. Requires company demographics, segmentation rules, baseline eNPS, and target metrics. Endpoint: https://mcp.gapup.io
- esrs_narrative_builder - Builds ESRS/CSRD-compliant sustainability narratives for companies. Call when an agent needs to draft or refine a CSRD-ready report covering ESRS standards (E/S/G) with double-materiality analysis, KPIs, and audit-ready cross-references. Returns a structured narrative document including material topics, quantified KPIs, assurance readiness status, and identified audit gaps. Requires company profile (name, sector, financials), applicable ESRS standards, countries of operation, and raw ESG data (e.g., emissions, workforce metrics, supply chain details). Endpoint: https://mcp.gapup.io
- event_marketing - Generates an optimized event marketing plan to maximize MQLs and pipeline from a fixed annual budget. Call it when planning next year’s events or reallocating spend mid-year. Returns a prioritized list of 6-10 events (salons, webinars, conferences) with budgets, execution phases, and KPIs (cost/MQL, MQLs generated, pipeline impact). Requires company profile, annual budget, current event performance, and sales cycle length. Endpoint: https://mcp.gapup.io
- fraud_detector - Analyzes financial transactions, supplier invoices, and expense reports to detect fraud patterns. Call it when validating high-risk transactions or reviewing monthly financial activity. Returns a structured report with detected anomalies, risk amounts, and prioritized alerts. Requires company profile, transaction volumes, and raw transaction data as input. Endpoint: https://mcp.gapup.io
- funding_hunter - Scans and scores all public funding opportunities (grants, loans, tax credits, equity matches) available to a company’s profile, prioritizing volume and deadlines. Call this when an agent needs to build a mid-funnel pipeline of 30+ matched funding sources for a cleantech/deeptech industrial SME in France. Returns a structured report with KPIs (total non-dilutive funding, quick-wins, pipeline mix, success probabilities, and cash timelines) and a ranked list of top 30 devices with eligibility checks and deadlines. Requires company pitch, sector, HQ country, SIRET, and founding year. Endpoint: https://mcp.gapup.io
- geographic_expansion - Evaluates and sequences new geographic markets for expansion based on company, product, and financial inputs. Agents should call this when assessing market entry feasibility, ROI, and optimal market order. Returns a prioritized market sequence with projected ARR, investment breakdown, and GTM timelines. Requires company sector, current markets, product details, financials, and target countries. Endpoint: https://mcp.gapup.io
- growth_path_architect - Designs a 36-month growth plan to scale ARR from current to target, including primary growth drivers (organic, geo, partnerships), budget allocation, and M&A triggers. Call when a CSO needs a data-backed roadmap with quantified KPIs, budget splits, and execution milestones. Returns a structured plan with target ARR, growth mix, budget breakdown, and 5+ KPIs (e.g., CAGR, contribution splits, ROI). Requires company profile (sector, ARR, geographies, team size), growth target (ARR, horizon, budget), and current growth drivers (contribution %, growth rate %). Endpoint: https://mcp.gapup.io
- insurance_coverage_analyzer - Analyzes current insurance policies to identify coverage gaps, benchmark premiums, and generate an RFP template for insurers. Call when evaluating risk exposure for a company or preparing for due diligence. Returns a structured report with a coverage score, identified gaps, premium benchmarks, and an RFP template. Requires company details, financial metrics, sector, jurisdiction, and current policy data as input. Endpoint: https://mcp.gapup.io
- internal_communication - Generates a 90-day internal communication plan for large organizations. Call it when leadership needs a structured rollout of strategic messaging across multiple geographies and employee segments. Returns a JSON report with KPIs (e.g., eNPS delta, cascade time), channel portfolio, playbooks per audience, crisis comms templates, and an editorial calendar. Requires company size, sector, current maturity gaps, and target audience details. Endpoint: https://mcp.gapup.io
- investor_list - Generates a targeted investor list for a funding round, including warm introduction paths. Call it when preparing a Series A/B/C raise to identify 20-30 relevant VCs matching stage, ticket size, sector, and geography. Returns a structured list of investors with match scores, Tier A/B/C categorization, and actionable warm intro routes via existing investors or portfolio overlaps. Requires company name, sector, round details (stage, ticket range, geography), ARR, and existing investors. Endpoint: https://mcp.gapup.io
- investor_shortlist - Generates a targeted investor shortlist for a Series B fundraising round. Call it when you need a curated list of 16+ EU/US investors matched by stage, sector, thesis, and geography, including fit scores and warm intro paths. Returns a JSON object with investor details, fit metrics, warm intro opportunities, and estimated outreach timelines. Requires company profile, sector, growth metrics, fundraising plan, and target round size. Endpoint: https://mcp.gapup.io
- ip_protection_pilot - Analyzes a company’s patent portfolio in biotech (e.g., enzymatic PET/PEF recycling) to assess IP strength, licensing potential, and infringement risks. Call when evaluating deeptech firms with public patent filings (EP/US/FR) to quantify royalty opportunities, active patents, and litigation exposure. Returns a structured report with KPIs (e.g., granted/pending patents, €2-8M licensing potential, €3-12M infringement risk) and competitor benchmarks. Requires company details (name, sector, country) and patent portfolio summary (e.g., enzyme variants, filing jurisdictions, competitors). Endpoint: https://mcp.gapup.io
- knowledge_base_auto - Automatically builds a structured knowledge base from company data sources (Slack, Notion, Drive, Confluence, Salesforce). Call when an agent needs to consolidate fragmented internal knowledge into a searchable, categorized FAQ system. Returns a COO-grade report with integrated sources, auto-generated articles, KPIs (e.g., time-to-find-info <2 min), and a maintenance plan. Requires company metadata (name, sector, FTE) and access credentials/URLs for the specified sources. Endpoint: https://mcp.gapup.io
- kyc_screener - KYC/AML multi-jurisdiction screening across 6 sanctions lists (OFAC US, UN Consolidated, EU EEAS, UK HMT/OFSI, Swiss SECO, Canada OSFI, Australia AUSTRAC). Cross-source risk scoring, freshness per source, weekly refresh. Returns hits_by_source (which jurisdictions match), consolidated_risk_level (high if >=2 sources, medium if 1, low/clear otherwise), and freshness metadata per source. Use during client onboarding, transaction monitoring, UBO checks, or periodic AML refresh. Endpoint: https://mcp.gapup.io
- ld_architect - Designs a company-wide learning & development (L&D) program tailored to business needs. Call it when an agent must propose a concrete L&D plan with ROI metrics for a scaling organization. Returns a structured L&D plan including a catalog of 6-8 training modules, 3 personalized learning paths, and KPIs (investment, productivity gains, retention impact, payback period). Requires company profile (size, sector), team composition (departments, growth rate), and prioritized skill gaps (skill, priority, current coverage). Endpoint: https://mcp.gapup.io
- lead_magnets - Generates a complete lead magnet package (guide, landing page, nurture sequence, and promotion matrix) tailored to a defined ICP. Call when launching a new content asset to attract and qualify B2B leads. Returns a structured deliverable with KPIs, executive summary, and actionable assets. Requires an ICP definition (persona, industry, pain points) and case label for context. Endpoint: https://mcp.gapup.io
- ma_deal_screener - Screens M&A targets for a buyer based on strategic thesis and financial criteria. Call when an agent needs a shortlist of 10-12 AI infrastructure companies (ARR €5-60M) aligned with the acquirer's Agentforce roadmap. Returns a ranked list of targets with fit scores, valuation ranges, integration risks, and top synergies. Requires acquirer details (name, sector, ARR, thesis), screening criteria (geography, ARR range, entry mode), and focus areas (e.g., AI infra, observability). Endpoint: https://mcp.gapup.io
- margin_doctor - Analyzes each deal’s gross margin against a target, flags under-margined deals, and generates tailored negotiation scripts and a defensive pricing playbook. Call when reviewing a pipeline of 5+ deals with known COGS, discounts, or urgency to identify margin gaps and recovery opportunities. Returns a structured report with KPIs (e.g., deals under target, potential ARR recovery, margin delta) and per-deal scripts. Requires company/product context, target gross margin, and an array of deals with ARR, discount %, COGS, competitors, urgency, and closing date. Endpoint: https://mcp.gapup.io
- margin_doctor_finance - Diagnoses financial margin leaks and benchmarks them against sector peers. Call when ARR growth stalls or EBITDA margin falls below industry norms. Returns a structured report with margin scores, critical findings, and quantified leak amounts. Requires company financials (revenue, COGS, R&D, S&M, G&A, EBITDA) and cost breakdowns. Endpoint: https://mcp.gapup.io
- market_entry_strategist - Designs market entry strategies for global expansion. Call it when evaluating a new country or segment for product launch, partnership, or investment. Returns a structured plan including Porter 5 forces analysis, entry mode recommendations (JV, WOS, M&A, etc.), 18-month go-to-market roadmap, and risk register with quantified KPIs (TAM, SOM, capex, payback, MAU, headcount). Requires company profile (name, sector, size, home market, revenue) and target market details (country, rationale, regulatory context, competitive landscape). Endpoint: https://mcp.gapup.io
- market_sizing - Calculates TAM (Total Addressable Market), SAM (Serviceable Available Market), and SOM (Serviceable Obtainable Market) for a B2B SaaS product in Europe. Call when validating market size for fundraising, go-to-market strategy, or investor pitches. Returns a structured report with TAM/SAM/SOM values, CAGR, competitor benchmarks, and sensitivity analysis. Requires product details (name, category, value proposition), target geography, and customer segments. Endpoint: https://mcp.gapup.io
- marketing_roi_dashboard - Generates a marketing ROI dashboard analyzing channel performance, attribution, and optimization recommendations. Call when an agent needs to evaluate marketing spend efficiency, identify underperforming channels, or reallocate budget. Returns a structured report with KPIs (ROI, CPL, CAC), channel-specific metrics, and actionable recommendations. Requires company name, period, budget, revenue, and per-channel spend and conversion data. Endpoint: https://mcp.gapup.io
- meddic_scoring - Scores a sales pipeline using the MEDDIC framework, evaluating each deal across dimensions (metrics, economic buyer, decision criteria, etc.) to generate a weighted MEDDIC score and forecast. Call this when a sales leader needs an objective assessment of deal health, risk exposure, or commit/best-case revenue projections. Returns a structured report with pipeline totals, commit/best-case forecasts, ARR at-risk, and per-deal MEDDIC scores with evidence. Requires input data including company/product details, target win rate, sales cycle metrics, and deal-level MEDDIC dimensions. Endpoint: https://mcp.gapup.io
- onboarding_salaries - Generates structured onboarding salary benchmarks and operational playbooks for 5 common roles (Senior Backend Engineer, Account Executive Mid-Market, Customer Success Manager, Product Designer Senior, People Ops Manager) in mid-stage SaaS companies (~250 FTEs). Call when designing or optimizing onboarding programs to quantify productivity gains, cost savings, and bad-hire risks. Returns a report with KPIs (time-to-productivity, cost per employee, bad-hire avoidance) and 30/60/90-day checklists tailored to the company's tool stack (Slack, Linear, Salesforce, etc.). Requires company profile (name, sector, FTE count, funding stage, location, tool stack) and target roles. Endpoint: https://mcp.gapup.io
- operational_dashboards - Generates an operational dashboard blueprint for a company’s departments, including KPI definitions, data sources, and implementation roadmap. Call it when an agent needs to design or optimize real-time monitoring for business performance. Returns a structured report with KPIs, tool recommendations, and a phased deployment plan. Requires company context, department details, and current pain points as input. Endpoint: https://mcp.gapup.io
- outbound_sequencer - Generates multi-channel outbound sequences (email, LinkedIn, phone) tailored to 3 personas (CFO, CRO, CEO) for B2B SaaS targets in France/DACH/Benelux. Call when an agent needs a high-conversion cold outreach strategy with quantified KPIs (response rates, meetings, pipeline). Returns a structured report with 6-touch sequences per persona, A/B variants, and expected performance metrics. Requires ICP details (sector, company size, geography) and offer specifics (value prop, pricing, main benefit). Endpoint: https://mcp.gapup.io
- paid_ads_optimizer - Analyzes and optimizes paid ad campaigns across platforms (Google, LinkedIn, Meta, etc.) to reduce wasted spend and improve ROAS. Call it when an agent detects underperforming campaigns or misaligned budgets against targets like CAC or lead quality. Returns a structured report with wasted budget identification, projected ROAS improvements per platform, and a concrete reallocation plan. Requires campaign details (platform, budget, current ROAS, objectives) and company/sector context. Endpoint: https://mcp.gapup.io
- positioning_strategist - Defines a differentiated positioning strategy for a product or company. Call it when an agent needs to craft a clear, competitive market position, including a unique angle, messaging pillars, and an execution plan. Returns a structured positioning strategy with a differentiation angle, 5 messaging pillars, enemy definition, and a battle plan. Requires the company name, sector, current tagline, and main product features as inputs. Endpoint: https://mcp.gapup.io
- press_influencer - Generates a complete press kit for company announcements (fundraising, product launches, etc.), including a press release, tailored media lists (Tier 1-3), and a 14-day outreach plan. Call it when preparing a structured media campaign for a high-impact announcement. Returns a press kit with a draft press release, 12-20 targeted journalist contacts, a day-by-day diffusion calendar, and estimated KPIs (impressions, coverage, engagement). Requires company details, announcement type, headline, and key facts. Endpoint: https://mcp.gapup.io
- pricing_in_deal - Generates a pricing strategy for an active deal in negotiation stage, including deal scoring, risk assessment, and 3 concrete pricing scenarios with ROI calculations. Call when a sales rep needs to justify a counter-offer or pricing adjustment to close a deal. Returns a structured report with deal score, win probability, key risks, leverages, and 3 pricing scenarios (conservative, balanced, aggressive) with ROI and margin impact. Requires company details (name, sector, product, pricing model), deal context (prospect, stage, size, competitors, decision-maker), and current pricing data (list price, avg discount, budget constraints). Endpoint: https://mcp.gapup.io
- pricing_strategist - Generates a CMO-grade pricing strategy for B2B SaaS products, including tier structure, usage metering, and migration plans. Call when optimizing revenue, ARPU, or customer segmentation, or when introducing new features like AI/edge functions. Returns a structured report with pricing tiers, KPIs (ARPU delta, churn projection), competitive analysis, and migration roadmap. Requires company details (name, sector, ARR, ARPU), current pricing approach/pain points, and competitor pricing data. Endpoint: https://mcp.gapup.io
- privacy_compliance_audit - Performs a privacy compliance audit for a company, evaluating risks across RGPD, UK GDPR, CCPA-CPRA, and LGPD frameworks. Call this when an agent needs to assess legal exposure, identify gaps, and prioritize remediation for data processing activities, especially in cross-border data transfers (e.g., EU→US under Schrems II). Returns a structured report including KPIs (e.g., sanction exposure, treatment inventory, critical gaps, time-to-compliance estimate) and a prioritized action plan. Requires company details (sector, jurisdictions, revenue), processing activities, and existing compliance artifacts (e.g., DPO status, DPA notifications). Endpoint: https://mcp.gapup.io
- process_mapping - Maps operational processes to identify bottlenecks, inefficiencies, and improvement opportunities. Call when an agent needs to analyze a company's workflows (e.g., returns, inventory, customer service) to quantify time/cost savings or redesign processes. Returns a structured report with current vs. target KPIs (time, cost, FTE savings), payback period, and actionable recommendations. Requires company details (name, sector, FTE, locations, tool stack) and a list of processes with IDs, names, and descriptions. Endpoint: https://mcp.gapup.io
- process_mining - Analyzes business processes to identify inefficiencies, bottlenecks, and financial waste. Call this when an agent needs to quantify operational waste, validate process pain points, or generate optimization roadmaps for workflows. Returns a structured report with quantified waste (€/year), critical bottlenecks, quick wins, and automation opportunities. Requires input including company details, process names, departments, durations, step counts, involved roles, and current pain points. Endpoint: https://mcp.gapup.io
- procurement_spend_optim - Analyzes company spend data to identify cost-saving levers across suppliers and categories. Call when an agent needs to optimize procurement spend for a CFO or finance team. Returns a structured report with quantified savings opportunities, payback periods, and prioritized levers (e.g., consolidation, renegotiation). Requires company details (name, sector, FTE, revenue, total spend) and spend category breakdowns (category name, annual spend, supplier count, description). Endpoint: https://mcp.gapup.io
- proposal_generator - Generates a tailored commercial proposal for a prospect by analyzing company profiles, offer details, and contact information. Call it when preparing a sales pitch to a new or existing client to produce a structured proposal with ROI calculations and next steps. Returns a JSON object containing the generated proposal text, KPIs (ROI, payback period, time saved), and metadata like generation timestamp and case label. Requires input with company, prospect, and offer details including pricing, benefits, and contact information. Endpoint: https://mcp.gapup.io
- qa_pre_flight - Prepares a startup for investor Q&A by generating 30+ strategic questions (including 8 high-risk traps) and a 21-day preparation plan tailored to the company’s profile, fundraising round, and target investor profile. Call it when preparing for a Series C (or later) fundraising round to anticipate investor concerns and refine messaging. Returns a structured report with KPIs, question sets, and a step-by-step preparation timeline. Requires company details (name, sector, ARR, team size), round specifics (stage, target raise, investor profile), and founder pitch context. Endpoint: https://mcp.gapup.io
- qbr_auto - QBR automatique CSM — Gapup agent-payable C-suite expertise (CRO). Returns a structured, audited deliverable. Reference case: Gapup Hub × Alan — QBR Q1 2026 · Health score 82/100 · Upsell €18k détecté · Renewal low risk. Inputs are validated server-side — send the documented case fields. Endpoint: https://mcp.gapup.io
- recruiting_architect - Designs end-to-end recruitment plans for hard-to-fill roles in EU tech. Call when hiring for senior engineering, product, sales, or customer success roles with time-to-hire >90 days. Returns a structured hiring plan including multi-channel sourcing strategy, employer branding recommendations, interview frameworks, candidate journey, and KPI targets (time-to-hire, cost-per-hire, NPS, acceptance rate). Requires company profile (name, sector, size, funding stage, location, employer brand strength) and role details (title, type, seniority, department, start date, mission points). Endpoint: https://mcp.gapup.io
- renewal_optimizer - Analyzes renewal pipelines to identify at-risk accounts and generates actionable playbooks. Call it when renewal deadlines are approaching (≤90 days) or churn signals appear. Returns a renewal plan with ARR at-risk breakdown, projected renewal rates, and prioritized actions per account. Requires account details (ARR, renewal date, health metrics, churn signals) and company/product context. Endpoint: https://mcp.gapup.io
- reputation_engine - Monitors brand reputation across multiple channels (Twitter, LinkedIn, G2, Trustpilot, news, Reddit) and scores sentiment, criticality, and share of voice. Agents should call it when brand risk signals (e.g., negative reviews, regulatory mentions, executive departures) require crisis preparedness or response. Returns a structured report with KPIs (sentiment score, actionable signals, share of voice), executive summary, and ready-to-use crisis playbooks (comms templates, escalation paths, monitoring stack recommendations). Requires brand name, keywords, target channels, industry context, and optional historical crisis data. Endpoint: https://mcp.gapup.io
- revops_architect - Designs end-to-end RevOps blueprints for B2B SaaS companies. Call it when revenue leakage exceeds 5% ARR, forecast accuracy is below 65%, or the revenue team scales beyond 50 reps. Returns a RevOps audit (maturity score, bottlenecks, leakage estimate, quick wins) and a functional architecture (data model, processes, tool stack, governance plan, 12-week implementation roadmap). Requires company profile, revenue team structure, current tech stack, and performance metrics. Endpoint: https://mcp.gapup.io
- rfp_tender_architect - Structures a compliant and competitive RFP response by generating mandatory sections (compliance, technical, commercial, references, team, planning, risks, pricing), win themes, competitor comparison matrix, and a price-to-win strategy. Call this when an agent needs to draft or refine a tender response for a public or private RFP, ensuring alignment with client positioning and RFP scope. Returns a structured RFP document with executive summary, KPIs, and deliverables. Requires RFP scope, client company, our positioning, and optional competitor data. Endpoint: https://mcp.gapup.io
- rse_policy_builder - Generates a comprehensive CSR (Corporate Social Responsibility) policy for a company, including governance, ESG pillars, responsible procurement, stakeholder engagement, KPIs, a 36-month action plan, and internal/external communication strategies. Agents should call this when a company needs a structured, ready-to-implement CSR framework aligned with its values, sector, and ambitions. Returns a 15-25 section policy document with executive summary, KPIs, risk assessments, and actionable roadmaps. Requires company details (name, sector, size, revenue, country), core values, and strategic ambitions as input. Endpoint: https://mcp.gapup.io
- sales_enablement_architect - Designs and audits Sales Enablement programs for B2B SaaS sales teams. Call it when a sales team lacks a playbook, has low quota attainment, or slow rep ramp time. Returns a maturity audit with critical gaps, quick wins, and a prioritized 8-module program (onboarding, battlecards, playbook, CRM optimizations) with projected ARR impact. Requires company size, sales team metrics (reps, ramp, attainment), and current enablement stack (CRM, playbook, onboarding). Endpoint: https://mcp.gapup.io
- sales_pipeline_forecast - Generates a sales pipeline forecast for B2B SaaS deals by analyzing current pipeline data, historical performance, and deal confidence levels. Call it when an agent needs a data-driven revenue projection for a specific quarter, including commit, best-case, and worst-case scenarios. Returns a structured output with total pipeline value, weighted commit amount, scenario-based forecasts, at-risk deal analysis, and coverage ratio against quota. Requires input company details (name, sector, FTE, ARR, quota), pipeline period, and a list of deals with attributes like deal ID, account, segment, amount, stage, days in stage, expected close date, and owner. Endpoint: https://mcp.gapup.io
- save_plays - Generates a 30-day customer retention plan for at-risk accounts showing high churn risk. Call when an account signals departure (e.g., usage drop, champion change) and churn risk is validated. Returns a structured plan with KPIs (ARR at risk, save probability, action timeline, concession value) and executable scripts (6 actions × 4 concessions). Requires company/account details, churn reason, and churn signals. Endpoint: https://mcp.gapup.io
- strategic_options_analyzer - Models 5 strategic options for a company at a crossroads (pivot, expansion, new model, AI-native) and evaluates them using NPV, IRR, and payback metrics. Call when an agent detects a strategic inflection point (e.g., post-funding, market shift, or leadership change). Returns a ranked list of options with GO/NO-GO recommendations, key metrics, and validation timelines. Requires company profile (name, stage, funding, HQ), strategic context (trigger event, market conditions), and optional constraints (budget, timeline). Endpoint: https://mcp.gapup.io
- supplier_esg_audit - Computes ESG scores (0–100) for suppliers across Environmental, Social, Governance, and Supply Chain dimensions, flags high-risk suppliers, and generates remediation plans plus a continuous monitoring framework. Call when an agent needs to assess supplier sustainability compliance, identify gaps, or prepare for EcoVadis certification. Returns a structured report with supplier-level scores, risk flags, remediation timelines, and a monitoring dashboard. Requires company profile, supplier list with spend data, and any existing ESG certifications or known issues. Endpoint: https://mcp.gapup.io
- sustainability_report - Generates a non-greenwashed sustainability report for B2B companies targeting labels like B-Corp, EcoVadis, or Lucie 26000. Call when an agent needs a narrative-driven, stakeholder-inclusive sustainability report with quantified KPIs and testimonials. Returns a structured report with executive summary, KPIs (e.g., B-Corp score, CO2e avoided, diversity metrics), and alignment with frameworks (EU Taxonomy). Requires company profile (name, sector, size, mission), existing labels, target labels, and sustainability pillars (environmental, social, governance). Endpoint: https://mcp.gapup.io
- sustainability_reporting_pilot - Generates a regulatory sustainability report draft for CSRD/SFRD compliance, targeting CAC/ComEx use cases. Call when preparing first-time CSRD filing (wave 2) for a private-large EU industrial SME. Returns a structured report with KPIs (e.g., ESRS datapoint coverage, compliance score, ESG rating, cost savings, filing timeline) and an executive summary. Requires company profile (name, sector, size, country), target frameworks, and governance/environmental data inputs (e.g., board composition, emissions, certifications). Endpoint: https://mcp.gapup.io
- tax_optimization - Calculates and recommends tax optimization strategies for a company based on its financials, activities, and jurisdictions. Call it when an agent needs to identify eligible tax credits (e.g., CIR, IP Box), holding structures, or regime-specific savings to reduce tax liability. Returns a structured report with KPIs (e.g., €2.4M annual savings), actionable steps, and implementation plans. Requires company details (sector, stage, legal form), financials (revenue, EBITDA, R&D spend), jurisdictions, and activity descriptions. Endpoint: https://mcp.gapup.io
- term_sheet_negotiation - Analyzes and scores term sheet clauses for a funding round, identifies negotiation risks, and generates a founder-friendly counter-proposal strategy. Call it when an agent needs to evaluate term sheet fairness, prioritize negotiation targets, or prepare a structured negotiation plan. Returns a scored analysis with KPIs (e.g., founder-friendly score, clause risk levels), concrete counter-proposals per clause, and a 3-phase negotiation strategy. Inputs required: company name/sector, round details (stage, amount, lead investor, pre-money valuation), and the term sheet clauses with current text. Endpoint: https://mcp.gapup.io
- treasury_optimizer - Calculates an optimal cash allocation strategy for corporate treasuries. Call when a CFO needs to maximize yield on idle cash while respecting risk appetite, liquidity constraints, and bank partner limits. Returns a 12-month cash flow calendar, instrument allocation breakdown (e.g., MMFs, term deposits, T-bills), projected yield uplift, and implementation plan per bank. Requires company cash position, operational reserve needs, currency exposure, risk tolerance, and bank partner constraints. Endpoint: https://mcp.gapup.io
- upsell_hunter - Identifies high-potential upsell opportunities for existing accounts by analyzing usage signals, contract status, and product fit. Call this tool when an agent needs to prioritize accounts for expansion revenue or prepare renewal negotiations. Returns a ranked list of accounts with upsell recommendations, potential revenue impact, and actionable playbooks. Requires company details, product offerings, and account-level data (e.g., ARR, tier, usage, NPS). Endpoint: https://mcp.gapup.io
- vendor_management - Analyzes a company's vendor portfolio to identify cost-saving opportunities, risks, and negotiation priorities. Call when reviewing procurement spend, contract renewals, or vendor consolidation. Returns a structured report with total spend breakdown, identified savings (€), high-priority renegotiation candidates, consolidation opportunities, and risk assessments. Requires company details (name, sector, total vendor spend) and a list of vendors with spend, contract end dates, satisfaction scores, criticality levels, and single-source flags. Endpoint: https://mcp.gapup.io
- vendor_risk_assessor - Evaluates vendor risk across cyber, financial, operational, regulatory, and concentration dimensions. Call when performing annual reviews, contract renewals, or spend consolidation for regulated or critical suppliers. Returns a prioritized remediation plan with KPIs (e.g., critical vendor count, concentration risk, spend breakdown) and a heatmap. Requires company details, assessment purpose, risk framework, and vendor data (spend, criticality, certifications, issues). Endpoint: https://mcp.gapup.io
- win_loss_decoder - Analyzes historical win/loss deals to extract patterns, drivers, and competitive insights. Call this when evaluating deal performance, diagnosing pipeline gaps, or designing CRO playbooks. Returns a structured report with KPIs (win rate, lost value), competitive analysis, and tactical recommendations (e.g., SSO integration, nurture sequences). Requires input: company/product context, deal outcomes (won/lost), values, durations, competitors, and notes. Endpoint: https://mcp.gapup.io
- working_capital - Calculates and optimizes working capital (BFR) by analyzing DSO, DPO, and DIO against sector benchmarks. Call it when a CFO needs to identify cash liberation opportunities, prioritize quick wins, and generate a 90-day actionable roadmap. Returns a structured report with current vs. target KPIs (DSO/DPO/DIO), cash freed, and prioritized quick wins with negotiation scripts. Requires company financials (revenue, AR, AP, cash), current DSO/DPO/DIO days, and sector context. Endpoint: https://mcp.gapup.io
- statement_auditor - LP Statement Auditor — Gapup agent-payable C-suite expertise (CFO). Audits LP capital account statements across fund vehicles before distribution, flagging carried interest waterfall errors, FX compliance issues, management fee base transitions, and cross-fund NAV inconsistencies. Call it when a fund manager needs to pre-flight LP statements for 20+ LPs across multi-vehicle structures before sending a distribution. Returns a structured audit report with anomaly register, ILPA/ASC 946/IFRS 10 compliance findings, and distribution approval status. Reference case: Q4 2026 — 47 LPs, 3 fund vehicles, $2.3B AUM, 12 anomalies flagged pre-distribution. Inputs are validated server-side — send the documented case fields. Endpoint: https://mcp.gapup.io
- valuation_reviewer - Revue de valorisations GP — Gapup agent-payable C-suite expertise (CSO). Reviews GP valuation packages for LP reporting, validating methodology consistency (DCF, revenue multiples, last-round, precedent transactions), cross-checking mark-up/mark-down rationale, peer comparables, and exit assumptions. Call it before sending quarterly GP packages to LPs, or when the LP committee flags unusual portfolio movement. Returns a structured review report with per-company findings, methodology flags, and an overall portfolio drift analysis vs public benchmarks. Reference case: Q3 2026 GP package — 12 portfolio companies cross-fund $4.2B AUM, mark-to-market pre-LP. Inputs are validated server-side — send the documented case fields. Endpoint: https://mcp.gapup.io
- cash_forecast_18m - Prévisions de trésorerie 18 mois — Gapup agent-payable C-suite expertise (CFO). Builds a rolling 18-month cash forecast with base, stress, and upside scenarios, covenant watch alerts, working capital sensitivity, and a tornado analysis of the top 5 cash drivers. Produces a lender-ready bridge from P&L to cash. Call it when a company needs visibility on liquidity under multiple macro assumptions, faces an upcoming debt covenant test, or is preparing a bank package. Distinct from financials-monte-carlo (probabilistic MRR) and bp-narratif (narrative deck). Reference case: Back Market — forecast trésorerie 18m post-restructuring Q3 2023. Inputs are validated server-side — send the documented case fields. Endpoint: https://mcp.gapup.io
- financials_monte_carlo - Modélisation financière Monte Carlo — Gapup agent-payable C-suite expertise (CFO). Produces a Monte Carlo simulation summary synthesizing 10,000+ runs into P10/P50/P90 revenue and cash trajectories, a sensitivity tornado on the top input drivers, and a three-scenario tree (pessimistic/base/optimistic) over a configurable horizon (up to 36 months). Call it when a startup or growth company needs probabilistic financial projections grounded in real business hypotheses for investor presentations, board packages, or fundraising. Reference case: Stripe — Monte Carlo 36 mois post-Series A 2012. Inputs are validated server-side — send the documented case fields. Endpoint: https://mcp.gapup.io
- due_diligence_dossier - Dossier de due diligence — Gapup agent-payable C-suite expertise (FUNDRAISING). Produces a fundraising-grade due diligence package: full DD checklist across 8 categories (legal, financial, technical, commercial, HR, IP, regulatory, ESG), gap analysis with risk amplifiers, 50+ anticipated investor Q&A, and a prioritized remediation plan with timeline. Call it when a startup preparing a Series A, B, or C raise needs to get a dataroom DD-ready before meeting tier-1 investors — compressing 4-8 weeks of prep to 1 week. Reference case: Aleph AI Series B — dataroom DD-ready 100% checklist 8 catégories · Q&A préparé · gaps identifiés. Inputs are validated server-side — send the documented case fields. Endpoint: https://mcp.gapup.io
- ma_integration_playbook - Playbook d'intégration M&A — Gapup agent-payable C-suite expertise (CSO). Produces a post-merger integration playbook covering workstream mapping, Day-100 plan, revenue and cost synergy sizing, risk register with mitigations, SteerCo governance structure, communications plan, and cultural integration + retention strategy. Call it immediately after deal close when the acquirer needs a structured 12-18 month integration roadmap to preserve deal value and hit synergy targets. Reference case: Cas démo — Playbook d'intégration M&A. Inputs are validated server-side — send the documented case fields. Endpoint: https://mcp.gapup.io
- matrice_materialite - Matrice de matérialité — Gapup agent-payable C-suite expertise (SUSTAINABILITY). Produces a CSRD-compliant double-materiality matrix: applies ESRS sector topics, builds a long list (30+ topics), scores each on financial impact and sustainability impact (IRO — impacts, risks, opportunities), synthesizes stakeholder consultation inputs, prioritizes the top 8-12 material topics, and delivers an action plan. Call it when a company must run its first ESRS-2 double-materiality assessment for CSRD reporting or update a prior GRI-only matrix to CSRD standards. Reference case: Decathlon France — matrice double-matérialité 2026 · 28 topics longue liste · 12 prioritisés · IRO mapping · stakeholder consultation. Inputs are validated server-side — send the documented case fields. Endpoint: https://mcp.gapup.io
- russian_compliance_secondary - Advanced Russian sanctions compliance for bank compliance officers, export control teams, and EU/US/UK regulated entities. Covers secondary sanctions mechanics not handled by direct SDN screening:

• ownership_chain — OFAC 50% Rule (FAQ 401): evaluates beneficial ownership cascade to detect indirect SDN exposure. Blocked if ≥50% cumulative sanctioned ownership. Accepts array of UBOs with percentage.
• article_5n_check — EU Regulation 833/2014 Article 5n (13th package 2024-02-21): checks if providing a service (accounting/audit/legal/IT/PR/architecture/engineering/consulting) to a Russian-nexus entity is prohibited.
• general_licence_check — UK HMT/OFSI general licences: identifies applicable UK general licences for the scenario (humanitarian, divestment, legal fees, journalism, diplomatic, etc.).
• price_cap_check — G7 oil price cap mechanism: crude $60/bbl, premium products $100/bbl, discount products $45/bbl. Returns whether attestation chain is required.

Output: overall_risk (low/medium/high/prohibited), P0/P1/P2 signals, mode-specific structured results. No external API required. Static rules encoded from OFAC, EU Eur-Lex, UK legislation.gov.uk, US Treasury. Endpoint: https://mcp.gapup.io
- fx_rate - Get the current or historical foreign-exchange rate for any currency pair — the exact exchange rate, FX rate or conversion rate an agent needs to convert a currency amount or feed a finance, trading, invoicing or pricing workflow. Covers EUR/USD, USD/JPY, GBP/EUR and every ISO-4217 currency pair. Returns the latest spot rate, or a historical rate by date. Use when a workflow needs a precise live or past currency exchange rate, or to convert money between two currencies. Source: European Central Bank reference rates via Frankfurter. Inputs: from/to ISO-4217 currency codes, optional date (YYYY-MM-DD). Endpoint: https://mcp.gapup.io
- realtime_data_streams - High-frequency real-time market data for trading agents, market-making bots and fintech analysts. Returns FX ticks (bid/ask/spread), intraday OHLCV candles, crypto orderbook snapshots (depth 5-50), recent trades with VWAP, and sovereign bond yields. All sources are keyless public REST APIs (Binance, Coinbase, Kraken, OKX, open FX feeds, worldgovernmentbonds.com). Ultra-short cache: 10s for ticks/trades, 60s for orderbook. Use when an agent needs live market data as precise numeric inputs for trading logic, arbitrage detection, or portfolio valuation. Endpoint: https://mcp.gapup.io
- interest_rate - Return a precise reference interest rate — the exact figure an agent injects into a treasury, lending, valuation or trading model. Available rates: fed_funds, sofr, us_10y, us_2y, us_3m, ecb_main, euribor_3m. Source: FRED (Federal Reserve Bank of St. Louis). When to use: an agent's computation needs a current benchmark rate as a precise input. Endpoint: https://mcp.gapup.io
- economic_indicator - Return a precise macroeconomic indicator for a country — the exact figure for a market-sizing, finance or strategy workflow. Indicators: gdp_usd, gdp_per_capita, gdp_growth, inflation, unemployment, population. Source: World Bank. When to use: an agent's analysis needs an authoritative country-level economic figure. Inputs: country (ISO-2 or ISO-3 code) and indicator name. Endpoint: https://mcp.gapup.io
- corporate_registry_lookup - Resolve legal information about a company from its national corporate registry. Returns a normalised, sourced company profile: legal status, registration number, directors, shareholders, recent filings, registered address, share capital, and a quality score (0–100). Coverage: France (INPI, keyless — full SIREN/SIRET with directors), 3M+ entities worldwide via GLEIF LEI (keyless, large companies), UK (Companies House, optional key), Netherlands (KvK, optional key), and OpenCorporates (token required since 2026). Sources are tried in cascade; quality_score increases with each source that succeeds. When to use: due-diligence, KYC screening, supplier verification, M&A research, or any workflow needing verified company identity and legal status. Optional env vars: COMPANIES_HOUSE_API_KEY (UK), KVK_API_KEY (NL), OPENCORPORATES_API_TOKEN (OpenCorporates token). Endpoint: https://mcp.gapup.io
- court_filings_multi - Aggregate court filings, judgments and litigation records for a company or individual across five major legal jurisdictions: US (CourtListener / PACER), UK (National Archives — EWHC/EWCA/UKSC/UKUT), EU (ECHR HUDOC — European Court of Human Rights), France (Légifrance / Cour de cassation) and Germany (BGH / BVerfG). Returns structured case records with type classification (civil/criminal/antitrust/bankruptcy/administrative/unknown), status (filed/pending/decided/appealed/unknown), parties extracted from case titles, opinion URLs and verbatim snippets. Cross-case pattern recognition produces severity-ranked signals (P0–P2) for criminal, antitrust, bankruptcy, regulatory, data-breach and IP categories. Use when: due diligence on a counterparty, vendor risk assessment, competitive intelligence (litigation history), regulatory exposure mapping. All sources are public and keyless. Optional env var COURTLISTENER_API_KEY raises US rate limits beyond the default 5 req/s anonymous tier. SLA: ≤25s p95 (all jurisdictions fetched in parallel, 8s budget per source). Quality score: 20 pts per jurisdiction with ≥1 case retrieved, +10 if signals detected, +5–10 if ≥2–3 distinct sources contributed. Endpoint: https://mcp.gapup.io
- gov_procurement_multi - Aggregate public procurement tenders (calls for tender / appels d'offres) from multiple government sources simultaneously: TED Europa v3 (27 EU countries, keyless API), BOAMP France (opendatasoft, keyless), UK Contracts Finder (OCDS standard, keyless), SAM.gov United States (requires SAM_GOV_API_KEY env var), and bund.de Germany (HTML scraping, partial). Returns structured tender records with buyer authority, EU CPV sector code, estimated contract value converted to EUR via live FX rates, submission deadlines, and direct notice URLs. Use when: a B2G agent needs to find government contract opportunities matching keywords across multiple jurisdictions; building a pipeline of public tenders for bid/no-bid qualification; monitoring a domain by CPV code; market sizing public sector spend. Key inputs: query (keywords), countries (ISO-2 array), cpv_codes (EU standard codes, e.g. 72000000=IT services, 45000000=construction, 79000000=business services), min_value_eur (filter), published_after (ISO date, defaults to 30 days ago). SLA: <=25s p95 (all sources fetched in parallel, 8s budget per source). Optional env var SAM_GOV_API_KEY enables US federal tenders (free key at api.sam.gov). Quality score: 25 pts if TED EU retrieved, 15 pts per other source retrieved (max 60), 10 pts if >= 10 tenders returned, 5 pts if aggregates computed. Status: failed < 30 / partial 30-59 / final >= 60. Endpoint: https://mcp.gapup.io
- web_search_multilang - Multi-language, multi-source web search that goes beyond Anglo-centric results. Supports 15 languages (fr/de/es/it/pt/nl/ja/zh/ko/ar/ru/sv/pl/tr/en) with automatic detection. Aggregates results from Mojeek (independent search engine, multilang) and Wikipedia (native multilang API), with DDG and HN as English-language complements. Returns deduplicated results ranked by cross-engine consensus. Use when you need non-English search results, when DDG fails, or for geographically-biased queries. Phase 2 #7 of the geo/lang expansion plan. Note: Brave/Bing/Searx are blocked from DO IPs — configure AICI_RESEARCH_PROXY_URL for residential proxy. Endpoint: https://mcp.gapup.io
- cve_security_lookup - Look up CVE vulnerability data for enterprise security teams, DevSecOps and SOC analysts. Supports two modes: exact CVE ID lookup (e.g. 'CVE-2024-3094') or keyword search by product/vendor (e.g. 'openssl', 'Apache Tomcat'). Cross-references four authoritative keyless sources: NVD NIST (official CVE database, CVSS v3 scores, affected CPEs), CISA KEV (Known Exploited Vulnerabilities catalog — exploit_in_wild flag), EPSS FIRST (exploit probability 0-1), GitHub Security Advisories (ecosystem-specific: npm/pypi/maven). Returns structured vulnerability records with CVSS v3 scores, affected product version ranges, CWE weakness classification, references and exploitation status. Signals engine produces P0/P1/P2 alerts: P0=CVSS>=9 + active exploitation, P1=CVSS>=7 or EPSS>=70%, P2=CWE pattern clusters. Relevant for EU NIS2 and DORA supply chain risk obligations. Optional env: NVD_API_KEY (raises NVD rate-limit 5→50 req/30s), GITHUB_TOKEN (raises GHSA GraphQL rate-limit). Cache TTL 6h. SLA <=25s p95. Endpoint: https://mcp.gapup.io
- dependency_vulnerability_scan - SCA (Software Composition Analysis) — scans a project dependency manifest and returns known vulnerabilities for each dependency. Supports: package.json (npm), requirements.txt (Python), go.mod (Go), Cargo.toml (Rust), composer.json (PHP), Gemfile.lock (Ruby), CycloneDX SBOM JSON. PRIMARY source: OSV.dev (keyless, free, covers npm/PyPI/Go/crates.io/Packagist/RubyGems + GHSA advisories federated). CVSS enrichment: NVD NIST (when OSV lacks score). Exploitation flag: CISA KEV (known-exploited-vulnerabilities catalog). Returns per-vuln CVE/GHSA IDs, severity, CVSS score, fixed version, and actionable upgrade recommendations. Relevant for EU NIS2 supply chain risk obligations, DORA, SOC 2 vendor assessments. Cache TTL 6h. Parallel OSV queries (concurrency=10). SLA <=30s p95. Endpoint: https://mcp.gapup.io
- patent_landscape - Search, analyze and map patent landscapes across major jurisdictions (US, EP, WO, CN, JP, KR). Three modes: (1) search — find patents by keywords, company name or inventor name; (2) landscape — aggregate distributions: top assignees, top inventors, CPC class breakdown, filings by year, citation leaders, white-space innovation opportunities; (3) lookup — retrieve a specific patent by number (e.g. US10000000B2, EP3456789A1, WO2023/123456). Primary source: WIPO PatentScope (WO PCT, keyless). Optional sources: USPTO PatentsView (US, env PATENTSVIEW_API_KEY), EPO OPS (EP/WO, env EPO_OPS_CONSUMER_KEY + EPO_OPS_CONSUMER_SECRET), Lens.org (global, env LENS_API_TOKEN). Use cases: freedom-to-operate (FTO) analysis, R&D gap identification, VC due diligence IP audit, competitor patent portfolio mapping, inventor network analysis. SLA: <=24s p95 (parallel fetches, 8s per source). Cache: 24h TTL (patent data stable). Quality score: 30 pts per retrieved source (max 90), +10 if >=10 patents, +10 bonus for landscape mode with non-empty top_assignees. Endpoint: https://mcp.gapup.io
- weather_climate_intel - Physical climate intelligence for insurance underwriting, agritech, logistics, energy trading and ESG/climate risk disclosure. Three modes: (1) forecast — 14-day daily weather forecast with temperature, precipitation, wind and humidity; (2) historical — daily records and monthly aggregates for any date range since 1940, with anomaly detection (P90/P95 heat events, extreme precipitation days); (3) climate_risk — long-term physical risk scoring combining CMIP6 ensemble projections (2020-2050), altitude, FEMA flood zones (US) and historical baselines. Risk dimensions: flood, heat (days >35°C/year), drought (SPI), wildfire, sea-level. Overall score 0-100 (100 = severe). Location: city string or lat/lon coordinates. Sources: Open-Meteo (keyless, global, 1940→2050), Open-Elevation, FEMA NFHL (US), NOAA CDO (optional NOAA_API_KEY env var for US+global station data). SLA: ≤25s p95. Cache: 1h forecast / 24h historical / 7d climate_risk. Endpoint: https://mcp.gapup.io
- real_estate_intel - Real estate intelligence aggregator with a best-in-class French dataset (DVF — Demandes de Valeurs Foncières — 100% of FR transactions since 2019, public, keyless) plus UK Land Registry Price Paid (all UK transactions 1995+). Four modes: (1) property — full transaction history for a specific address; (2) comparables — median/std price/m² within a radius (default 500m); (3) market — annual price series, YoY change, volume, trend by commune; (4) valuation — two-method estimate (comparables median + hedonic regression if n≥30) with confidence scoring (high/medium/low). All sources are free and require no API key. ICP: PropTech agents, REITs, fund managers, family offices, insurance. SLA: ≤25s p95 (sources fetched in parallel, 8s budget each). Cache: 24h TTL (DVF data is stable). Quality score: 30 pts DVF retrieved, 20 pts geocoding, 20 pts UK LR retrieved, 15 pts if comparables count ≥10, 15 pts if method quality achieved. Status: failed/<60/≥60 → failed/partial/final. No env vars required. Endpoint: https://mcp.gapup.io
- clinical_pharma_intel - Clinical and pharmaceutical intelligence for biotech analysts, healthcare fund managers, pharma BD teams, catalyst-driven hedge funds and health journalists. Aggregates live data across five modes:
• trials — active/completed clinical trials (ClinicalTrials.gov v2 + EU CTR in parallel, 450k+ records)
• pipeline — full pipeline by sponsor: trial count by phase + top indications
• approvals — FDA drug label approvals + mechanism of action (OpenFDA)
• recalls — FDA enforcement recalls classified by severity (Class I/II/III)
• adverse_events — FAERS aggregated reactions: top 10 reactions + serious% 

Signal detection (P0/P1/P2):
  P0 if Class I recall OR trial terminated for safety reason
  P1 if serious adverse events >30% OR ≥3 recalls in 12 months
  P2 otherwise (standard monitoring)

All sources are public and keyless. Optional env OPENFDA_API_KEY raises daily quota from 1,000 to 120,000 requests. SLA: ≤16s p95 (parallel fetch, 8s budget per source). Cache: 6h trials, 24h approvals, 12h recalls, 6h adverse events. Endpoint: https://mcp.gapup.io
- usdc_x402_payments_intel - Real-time analytics on x402 protocol USDC micropayments for MCP endpoints on Base network. Unique competitive advantage: aggregates internal production telemetry (our own traffic data) with on-chain USDC Transfer events and Bazaar marketplace listings — data no external competitor can access. Four modes: (1) facilitator_stats — Coinbase x402 facilitator settlement statistics (volume, count, top payees/payers). Uses Coinbase CDP API if COINBASE_X402_API_KEY is set; falls back to Base mainnet RPC scan of USDC transfers to known facilitator addresses. (2) endpoint_intel — Per-MCP-endpoint analytics: tx count, USDC volume, unique callers, success rate, catalog size. For gapup-mcp.io endpoints: reads internal JSONL telemetry (richest data source, unique). (3) agent_caller_profile — Anonymous profile of a calling agent wallet: tx count, USDC spent, top endpoints, inferred persona (depth-seeker / bulk-scanner / generalist / researcher / explorer). Wallet anonymised via SHA-256. (4) price_radar — USDC price distribution by tool category (data_lookup / synthesis / compliance / competitive) from Bazaar + internal catalog. Returns median, P25, P75. Network: Base mainnet. USDC contract: 0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913. Cache: 30 min LRU. Timeout per source: 8s. Optional env: COINBASE_X402_API_KEY (higher-fidelity facilitator stats). Endpoint: https://mcp.gapup.io
- sci_literature_search - Recherche bibliographique multi-sources sur la litterature scientifique. Sources : OpenAlex (200M+ works) · Semantic Scholar · arXiv · PubMed · CrossRef. Modes : search | meta_analysis | citation_network | expert_finder. Keyless / free tier. Cache LRU 12h. Endpoint: https://mcp.gapup.io
- patent_landscape_async - Async extended variant of patent_landscape. Supports max_results up to 200 (vs 50 in sync mode) and an optional include_citation_graph flag that enriches each patent with its 2-level citation graph (parent patents that cite this one + child patents cited by this one). Returns immediately (<300ms) with a job_id. Poll the result with patent_landscape_result(job_id) after eta_seconds (~180s). Use for deep R&D white-space analysis, freedom-to-operate (FTO) audits, VC due diligence IP mapping, or large-scale competitor portfolio analysis. Async tool — register a webhook via `webhooks_manage(register, url, [job.completed])` to receive callbacks instead of polling. Faster + lighter. Endpoint: https://mcp.gapup.io
- patent_landscape_result - Poll the result of a patent_landscape_async job. Returns status=pending while running, status=completed with the full patent landscape report once done, status=failed on error, or status=not_found if the job_id is unknown or expired (TTL 24h). Call this after the eta_seconds hint returned by patent_landscape_async (~180s). Endpoint: https://mcp.gapup.io
- china_market_data - Chinese capital market intelligence for the ZH diaspora (50M+) and institutional investors. Covers A-Shares (SSE/SZSE), H-Shares (HKEX), and ADRs across four modes:

• company — full company profile: name ZH/EN, USCC (18-digit social credit code), exchange, industry (CSRC classification), chairperson, registered capital, SOE flag
• market_quote — real-time quote: price (CNY or HKD), change%, volume, market cap, P/E ratio, dividend yield, last update timestamp
• sector_overview — sector snapshot: top 5 companies by market cap, avg P/E, 30-day sector index change. Supported sectors: semiconductor, ev, battery, technology, finance, energy, realestate, consumer, pharma, telecom
• regulatory_filing — recent regulatory disclosures (HKEX filings: annual, quarterly, announcements, mergers, IPOs) with title, date, document URL

Input formats accepted:
  • 6-digit A-Share ticker (e.g. '600519' for Moutai SSE)
  • HKEX ticker (e.g. '0700.HK' or '700' for Tencent)
  • Company name in EN or ZH (e.g. '腾讯', 'Kweichow Moutai')
  • Sector keyword (e.g. 'semiconductor', '半导体')

Data sources: Yahoo Finance (primary, always accessible), Eastmoney push2 + CompanySurvey (via Bright Data proxy when AICI_RESEARCH_PROXY_URL is set), HKEX filing API. Note: Eastmoney/CSRC/SSE are blocked from datacenter IPs without proxy — set AICI_RESEARCH_PROXY_URL to unlock full coverage. Endpoint: https://mcp.gapup.io
- india_market_data - Indian capital market intelligence for the IN diaspora (30M+) and investors. Covers NSE, BSE, and MCA corporate registry across four modes:

• company — full company profile: name, CIN, exchange, NSE/BSE tickers, industry, incorporation date, paid-up capital, registered office, status, directors
• market_quote — real-time quote: price (INR), change%, volume, market cap, P/E ratio. Sources: Yahoo Finance (primary), BSE API, NSE API (proxy-gated)
• sector_overview — Nifty/Sensex sector snapshot: top 5 companies by market cap. Supported sectors: it, banking, pharma, energy, auto, fmcg, realestate, metals, telecom, consumer
• mca_filing — Ministry of Corporate Affairs filings. Requires CIN for direct lookup.

Input formats accepted:
  • NSE ticker (e.g. 'RELIANCE', 'TCS.NS')
  • BSE 6-digit code (e.g. '500325' for Reliance)
  • CIN 21-char (e.g. 'L17110MH1973PLC019786')
  • Company name EN (e.g. 'Reliance Industries', 'Tata Consultancy')
  • Sector keyword (e.g. 'IT services', 'banking', 'pharma')

ENV: AICI_RESEARCH_PROXY_URL with country-in routing unlocks NSE direct API and MCA. Endpoint: https://mcp.gapup.io
- email_domain_health_check - Comprehensive email domain health check: MX routing, SPF authentication, DKIM signing, DMARC policy enforcement, DNSBL blacklist status (Spamhaus/SpamCop/Barracuda), TLS certificate validity, and WHOIS registration age. Aggregates a reputation score 0-100 and generates P0/P1/P2 deliverability signals. Accepts a domain (stripe.com) or email address (info@stripe.com). Detects role-based addresses (info@, support@, admin@, noreply@) that have higher bounce rates. Detects email provider (Google Workspace, Microsoft 365, Amazon SES, etc.). P0 signals: blacklisted / no MX / TLS expired / no SPF + DMARC none. P1 signals: SPF soft-fail / no DKIM selector / DMARC no reporting. P2 signals: role-based address / TLS expires <30d / domain age <90 days. All checks are keyless (no API keys required). Cache TTL 1h. SLA <=10s p95. Endpoint: https://mcp.gapup.io
- sharia_compliance_screener - Sharia compliance screening engine for Islamic banks, Sukuk issuers, Gulf sovereign funds, halal investment managers and MENA family offices. Zero competing MCP on this vertical.

Standards supported: AAOIFI (default) | MSCI_Islamic | S&P_Sharia | DJIM

Four modes:
• company — Full Sharia screen of a listed company: business activity (halal/haram/mixed) + AAOIFI financial ratios (debt/market-cap <30%, interest-assets <30%, non-compliant revenue <5%)
• instrument — Sukuk / halal fund classification by ISIN or name. Maps to known Sharia boards.
• sector_screen — Industry classification (halal/haram/mixed) with rationale + examples. Static AAOIFI-based map covering 40+ sectors.
• financial_ratios — AAOIFI ratio computation on fetched or provided financials.

Prohibited activities screened: alcohol, gambling, pork, weapons, pornography, tobacco, conventional banking (riba), conventional insurance, adult entertainment, embryonic stem cells.

Output includes compliance_status (halal/haram/doubtful_mixed/purification_required), purification_pct when applicable, P0/P1/P2 signals, quality_score, and sources. Endpoint: https://mcp.gapup.io
- geo_logistics_intel - Geospatial logistics intelligence for supply chain, maritime and transport agents. Four modes: (1) geocode_batch — resolve up to 50 addresses to lat/lon with confidence scores (OSM Nominatim + Open-Meteo fallback, 1 req/s rate-limit respected); (2) routing — road/cycling/walking route with distance_km, duration_seconds and ETA ISO timestamp between two addresses or lat/lon points (OSRM public, keyless, global); (3) port_congestion — congestion status for any UN/LOCODE port (e.g. NLRTM, SGSIN, CNSHA) with waiting vessel count, severity (low/medium/high/extreme) and average wait hours; (4) ship_tracking — AIS position, speed, course, destination and ETA for a vessel by its 9-digit MMSI. No API key required for geocode/routing/port. Optional env: AIS_STREAM_API_KEY for live ship data (otherwise MarineTraffic scrape best-effort). SLA: <=25s p95. Cache: 24h geocoding / 1h routing / 30min port / 5min ship. Quality score 0-100. Status: final/partial/failed. Endpoint: https://mcp.gapup.io
- tax_compliance_multi - Multi-jurisdiction tax compliance data for international SaaS, cross-border marketplaces and expat services. Five modes: (1) vat_lookup — validate EU VAT numbers live via VIES SOAP (27 EU countries) or UK VRN via HMRC; (2) sales_tax — US state sales tax rates, nexus thresholds (post-Wayfair 2018), digital goods taxability for all 50 states + DC; (3) gst — APAC GST/SST/consumption-tax rates for IN, SG, AU, NZ, MY, JP, KR, TH, ID, PH, VN with reduced rates and registration thresholds; (4) oss_ioss_eligibility — EU One-Stop-Shop and Import-OSS eligibility analysis (EUR 10k OSS threshold, EUR 150 IOSS per-consignment); (5) transfer_pricing_benchmark — OECD/JTPF operating-margin benchmarks by industry and country (20+ sectors, country-specific adjustments). Returns P0/P1/P2 compliance signals: P0=invalid VAT used for zero-rating, P1=taxable digital goods detected/audit risk, P2=filing deadlines/nexus alerts. Keyless — no API key required. Optional env: HMRC_VAT_API_KEY for UK VAT live validation. Cache TTL 24h. Endpoint: https://mcp.gapup.io
- talent_intelligence - HR tech intelligence for CHROs, recruiters, VC teams, comp & benefits leads and workforce planners. Four modes powered by ESCO, O*NET, BLS OES and crowd-sourced salary data:

• salary_benchmark — cash-only salary medians (p25/median/p75) for 54+ roles across US/EU/Asia. Covers tech, finance, compliance, healthcare, marketing, ops and C-suite. Data from BLS OES, Levels.fyi and StackOverflow Developer Survey 2024.
• skills_taxonomy — maps a skill to its ESCO URI, O*NET codes, skill type (hard/soft/knowledge/cert), 8 related skills with similarity scores and typical roles.
• job_market_trends — YoY growth %, open positions estimate, top employers and leading skills per job category × country. Static 2024 data with BLS baseline fallback.
• adjacent_roles — up to 6 roles adjacent to a source role with ESCO taxonomy adjacency: similarity score, salary delta % and skills overlap %.

All salary data is cash-only (excludes equity/RSU/bonus). Cache TTL: 24h (stable labour market data). Optional env ONET_API_KEY for authenticated O*NET lookups (free registration at onetcenter.org). Endpoint: https://mcp.gapup.io
- agoa_eba_intelligence - Intelligence préférentielle AGOA (US→Africa) et EBA/GSP (EU→Africa). Vérifie l'éligibilité d'un pays africain aux programmes tarifaires préférentiels, l'éligibilité d'un produit par code HS, identifie les meilleures opportunités d'export Afrique→US/EU, et fournit les règles de conformité (rules of origin, valeur ajoutée, docs). Différenciateur Africa diaspora : 39 pays AGOA + 47 LDCs EBA encodés. Sources : AGOA.info · EU EBA · EU GSP+ · WTO Tariff · UN Comtrade. Endpoint: https://mcp.gapup.io
- esg_audit_multi - Multi-mode ESG intelligence for ESG analysts, sustainability officers and impact investing fund managers. Aggregates live data from CDP, SBTi, Wikipedia, Yahoo Finance and web search across five modes:
• company_score — ESG score 0-100 with E/S/G breakdown + heuristic rating (AAA-CCC), from CDP grade + SBTi + sector profile
• controversy_check — controversies detected via web search, classified P0/P1/P2 by type (greenwashing, emissions fraud, labour, governance)
• emissions — GHG Scope 1/2/3 estimates, SBTi validation flag, net-zero target year, carbon intensity per M€ revenue
• esrs_readiness — CSRD gap across 12 standards (E1-E5, S1-S4, G1-G3): readiness % + gap list + CSRD deadline + effort man-days
• sfdr_classification — suggested SFDR Article 6/8/9 with rationale and sustainability indicators met

Signals: P0=critical (controversy/score<40), P1=significant (score<55/SBTi missing/ESRS<50%), P2=watch. Cache 24h. Endpoint: https://mcp.gapup.io
- financial_model_3statement - Pure-compute 3-statement financial model builder (Income Statement + Balance Sheet + Cash Flow). Feed assumptions (revenue growth, COGS%, OpEx, CapEx, working capital, tax rate, depreciation, debt schedule) → receive a full 3-5 year projection with integrated DCF valuation. Supports IFRS / US_GAAP / PRC_GAAP (中国会计准则) norms with bilingual ZH+EN labels for PRC. Modes: build (full 3-statement model) | scenario_analysis (base/bull/bear ±20% growth) | sensitivity (1 KPI × 1 input, 5-point grid). No external data needed — all computed from assumptions. ICP: VC due diligence, M&A analysts, CFO SMB, startup founders pitching investors, biotech/SaaS modeling. Returns balance_check_ok per year, DCF enterprise/equity value, and coherence warnings. Endpoint: https://mcp.gapup.io
- crypto_wallet_intel - Multi-chain on-chain analytics for crypto trading agents, on-chain analysts, AML/compliance teams and DeFi BD. Covers Ethereum, Base, Polygon, BSC, Arbitrum, Optimism — EVM-compatible addresses only.

5 modes:
• wallet_profile — full wallet summary: type (EOA/contract/CEX/protocol), inferred persona (whale/MEV-bot/DeFi-user/hodler…), age, tx count, native balance, ERC-20 count, NFT collections, OFAC sanctions flag
• token_flows — ERC-20 inflows/outflows per token on the selected period, priced in USD via CoinGecko
• pnl_estimate — FIFO realized + unrealized P&L on the period with confidence rating (high/medium/low)
• counterparties — top 20 counterparties ranked by USD volume with CEX/DEX/protocol labels
• defi_positions — active DeFi positions detected via Etherscan interaction history (Aave/Compound/Uniswap/Curve/Lido/Balancer/SushiSwap)

Signal detection (P0/P1/P2):
  P0 if OFAC SDN match OR direct Tornado Cash / sanctioned-protocol interaction
  P1 if >$1M volume on wallet <30 days old OR MEV-bot pattern OR >80% volume on single counterparty
  P2 informational (CEX wallet, new wallet, no anomaly)

Sources: Etherscan family (keyless free-tier, optional API key per chain), DefiLlama (keyless), public EVM RPC (keyless), CoinGecko free tier (keyless).
Cache TTL: 5 min (wallet activity evolves fast). Budget: 8s per source.

Env vars (all optional, raise Etherscan rate-limit from 1 req/5s to 5 req/s):
  ETHERSCAN_API_KEY · BASESCAN_API_KEY · POLYGONSCAN_API_KEY
  BSCSCAN_API_KEY · ARBISCAN_API_KEY · OPTIMISM_API_KEY Endpoint: https://mcp.gapup.io
- monte_carlo_portfolio - Pure-compute Monte Carlo portfolio simulation using Geometric Brownian Motion (GBM). Models a multi-asset portfolio across time with contributions, withdrawals, and annual rebalancing. Returns full probability distribution of terminal wealth, percentile paths, drawdown stats, and Sharpe ratio. Modes: simulate (full Monte Carlo) | glide_path (lifecycle 110-age target-date allocation) | stress_test (4 historical crises: 2008 GFC / 2000 dotcom / 1970s stagflation / 2020 COVID). No external data needed — all computed from asset assumptions. Ticker defaults built-in: SPY/VOO/VTI 7%/15%, QQQ 9%/20%, TLT/BND 3%/6%, GLD 5%/18%, BTC 30%/70%. ICP: asset managers, family offices, retail wealth advisors, robo-advisor agents, retirement planners. 10k simulations × 30 years runs in <3s on V8 JIT. Endpoint: https://mcp.gapup.io
- earnings_transcript_signals - Earnings call transcript signal extractor for equity research analysts, catalyst-driven hedge funds, and BD teams. Parses earnings transcripts (fetched or provided) to surface:

• signals (P0/P1/P2): guidance raise/cut, miss/beat vs consensus, buyback, dividend change, new product, executive change, capex shift, M&A intent, regulatory risk, competitive threat, supply chain, hiring
• kpis_mentioned: Revenue, EBITDA, EPS, FCF, Gross Margin, Operating Margin with YoY/QoQ %
• guidance: raised / maintained / cut / new_initiated items extracted
• q_and_a_topics: top Q&A themes detected (AI strategy, China exposure, M&A pipeline, macro, etc.)
• overall_tone: bullish / neutral / bearish

Sources fetched automatically: SEC EDGAR 8-K filings, Yahoo Finance earnings news, Motley Fool transcripts. Falls back to realistic mock transcript for testing if all fetches fail. Accepts transcript_text override for direct analysis. Supports multilingual transcripts (de/fr/es/zh). European tickers (SAP.DE, BMW.DE) mapped to EDGAR-compatible equivalents automatically. Endpoint: https://mcp.gapup.io
- arbitration_awards_lookup - Commercial arbitration intelligence for litigation lawyers, M&A due diligence teams, sovereign wealth funds and trade finance compliance. Covers 8 major institutions: ICC, AAA, LCIA, HKIAC, SIAC, CIETAC, DIAC, ICDR.

Three modes:
• party_lookup — find awards by party name (searches 20 landmark public awards + JusMundi best-effort)
• institution_index — browse awards and caseload stats per institution with date range filter
• clause_check — audit an arbitration clause for missing elements (institution, seat, language, arbitrator count, governing law, binding nature)

Note: Most arbitration awards are confidential. This tool surfaces public awards (Yukos, Crystallex, Achmea, etc.) plus redacted statistics from institutional annual reports. Private awards are not accessible.

Cache: 24h (arbitration data is very stable). No API key required. Endpoint: https://mcp.gapup.io
- ugc_moderation_classifier - Multi-language UGC content moderation for marketplaces, social platforms and comment systems. Detects policy violations in text content across 9 policies and 12 languages without external API calls.

Policies checked:
• hate — hate speech, slurs, dehumanization (50+ terms × 12 languages)
• sexual — explicit sexual content, pornography references, nudity solicitation
• violence — threats, weapon references, graphic violence
• self_harm — suicidal ideation, self-injury, eating disorder promotion
• harassment — doxxing, stalking, cyberbullying, blackmail
• scam — phishing, investment fraud, romance scam, lottery fraud
• spam — bots, keyword stuffing, excessive caps, emoji storms, suspicious URLs
• copyright — piracy, leaked content, serial keys, streaming fraud
• minor_safety — grooming signals, CSAM references, minor + adult content combos

Languages: en / fr / de / es / it / pt / nl / zh / ja / ko / ar / ru (auto-detected)

Output includes severity (low/medium/high/severe), confidence (0-100), matched patterns, excerpt, recommended action, age appropriateness (adult/teen/child), and signals.

No API key required. Stateless — no content is stored or logged. Endpoint: https://mcp.gapup.io
- china_ecommerce_intel - Chinese e-commerce intelligence for the ZH diaspora (50M+), import-export teams, brand IP enforcement, MENA/Africa entrepreneurs sourcing from China, and brand monitoring. Covers Taobao, Tmall, JD.com, Pinduoduo, 1688.com (B2B) and AliExpress (cross-border).

Five modes:
• product_search — search products by keyword across CN platforms. Returns title ZH/EN, price CNY + USD estimate, sales 30d, rating, seller info, product URL.
• seller_profile — full seller/supplier dossier: factory vs reseller detection, certifications (ISO, BSCI, CE), rating, years in business, main categories.
• price_history — 12-month price trend for a product (live current price + seasonal model for CN shopping festivals: 11.11, 6.18, CNY).
• brand_monitoring — detect counterfeits and grey market listings: price anomaly detection (>50% below MSRP = suspicious), counterfeit keyword scan, risk score 0-100.
• market_intel — category overview: top 5 sellers by market share, avg/median price, volume estimate, price range.

Data quality note: LIVE data from Taobao/Tmall/JD/Pinduoduo REQUIRES AICI_RESEARCH_PROXY_URL with CN residential routing (Bright Data -country-cn). Without proxy: AliExpress (cross-border) + curated category fallback available.

Input formats for seller_profile: 'platform:id' e.g. 'aliexpress:123456', '1688:87654321', 'tmall:apple-store-official'.
Input formats for price_history: AliExpress product URL or numeric product ID. Endpoint: https://mcp.gapup.io
- climate_scenario_rcp - Projections climatiques long terme par scénario IPCC (RCP AR5 + SSP AR6) pour toute localisation. Scénarios : RCP_4_5, RCP_8_5 (AR5), SSP1_2_6, SSP2_4_5, SSP3_7_0, SSP5_8_5 (AR6), ou 'all' (compare tous). Horizons : 2030–2100. Métriques : température (delta vs baseline 1990-2010, jours >35°C, nuits chaudes), précipitations (delta%, événements extrêmes, sécheresses), hausse du niveau de la mer (cm vs 2000), événements extrêmes (ouragans, inondations P100, sécheresses), indice incendie. Sorties : comparaison multi-scénarios, probabilité IPCC, signaux d'impact business par secteur. Sources : Open-Meteo CMIP6 (keyless), IPCC AR6 Atlas lookup, NOAA SLR projections. Usages : TCFD/CSRD physical risk, due diligence actifs long terme, assurance catastrophe, planification infrastructure. Cache 7j. SLA ≤20s. Endpoint: https://mcp.gapup.io
- job_postings_intelligence - Agrégation d'offres d'emploi publiques pour inférer les tendances de recrutement. Trois modes : (1) company_hiring — analyse des postings d'une société : volume, fonctions (engineering/sales/marketing/ops/finance/hr), seniorité, géographie, croissance vs période précédente, signaux stratégiques inférés ; (2) role_market — volume marché global pour un rôle (open positions estimate, top employeurs, compétences demandées, médiane seniorité) ; (3) competitor_hiring_comparison — comparaison multi-sociétés (total postings, growth%, focus areas). Sources : Adzuna (ADZUNA_APP_ID/KEY env), RemoteOK (keyless), Himalayas (keyless), baseline statique 40 top employeurs. Usages : due diligence VC, intelligence compétitive, benchmarks RH, signaux pivots stratégiques. Cache 6h. SLA ≤15s. Endpoint: https://mcp.gapup.io
- workflow_orchestrator - Meta-tool that CHAINS multiple MCP tools sequentially into a named workflow — delivering a composite output in a single call. 10 predefined workflows: compliance_full_audit (6 steps: KYC+sanctions+AI_gov+privacy+ESRS+CSRD), deal_due_diligence (7 steps: deep_dive+registry+court+patents+KYC+financials+M&A), market_entry_brief (6 steps: country_study+regulations+procurement+tax+AGOA+market_brief), competitor_intelligence_pack (5 steps: deep_dive+intel+patents+earnings+pitch_deck), esg_360 (5 steps: ESG_audit+carbon+CSRD+ESRS+supplier_esg), ip_freedom_to_operate (4 steps: patent_search+async_deep+IP_audit+competitive), climate_property_assessment (3 steps: climate_risk+real_estate+geo), pharma_target_screen (4 steps: trials+adverse_events+patents+meta_analysis), sanctions_360 (5 steps: KYC+Russian_sec+registry+crypto_wallet+court_filings), talent_market_brief (4 steps: salary+trends+adjacent_roles+skills_taxonomy). Returns steps_executed, consolidated P0/P1/P2 signals, overall_status, estimated_cost_usd, and raw outputs per step. Cache: 1h LRU per (workflow, target). Budget: 60s global timeout → partial if exceeded. Use when an agent needs a composite liverable without orchestrating tools manually. Endpoint: https://mcp.gapup.io
- historical_price_series - Fetch historical OHLCV price series for any ticker: stocks (AAPL, SAP.DE, 7203.T), ETFs, indices, commodities (GC=F for gold) or cryptocurrencies (BTC-USD). Returns a full date-indexed series of open/high/low/close/volume plus pre-computed statistics: total return, annualised return (CAGR), annualised volatility, max drawdown and Sharpe estimate (rf=4%). Automatically detects crypto tickers (→ CoinGecko) vs traditional assets (→ Yahoo Finance primary, Stooq fallback). Adjusts for dividends and splits when adjusted=true (default). Use cases: backtesting, factor analysis, performance attribution, charting, financial modelling. Sources: Yahoo Finance, CoinGecko, Stooq. All keyless. Optional env: AICI_RESEARCH_PROXY_URL for Bright Data routing (lifts Yahoo 429), TWELVE_DATA_API_KEY for higher Twelve Data quota. Endpoint: https://mcp.gapup.io
- candidate_screening_ranking - AI-powered candidate screening and ranking for recruiters, hiring managers, ATS providers and recruitment AI agents. Ingests a job description and 1-50 candidate resumes, returning a ranked shortlist with score breakdowns across five weighted criteria: skills_match (tech stack and soft skills extracted from JD vs resume), experience_match (years vs seniority level inferred from JD), education_match (degree level + top-school detection), role_progression (Junior to Senior to Lead patterns), culture_fit_estimate (remote/hybrid, startup vs enterprise). Per candidate: overall_score 0-100, matched/missing skills, red_flags (job hopping, employment gaps, seniority mismatch), green_flags (long tenure, promotions), 3-5 interview questions, fit_summary. Diversity signals are first-name proxies ONLY with mandatory ethical WARNING. All processing is local -- no external API calls, instant response, privacy-preserving. Endpoint: https://mcp.gapup.io
- legal_clause_extractor - Structured extraction of clauses, obligations and deadlines from legal documents (SaaS contracts, NDAs, employment agreements, loan agreements, leases, M&A deals, IP licences). Complements contract_risk_scanner with granular per-clause output.

ICP: legal ops, M&A lawyers, paralegals, contract managers, compliance officers.

Capabilities:
• Auto-detects document type (7 types) and language (EN/FR/DE/ES/PT)
• Extracts parties with roles (buyer, seller, licensor, employee, etc.)
• Splits document into sections and classifies 16+ clause types
• Per-clause: 20 obligation patterns (EN/FR/DE), 10 deadline patterns, 18 risk detectors
• Document-level: red flags (liability cap, auto-renewal, IP overreach, etc.), missing clauses per doc type
• Global deadline calendar with P0/P1/P2 severity
• Cross-reference map between sections
• Cache: 7 days (legal docs stable once provided)

100% pure compute — no external fetch required. Accepts 10k–100k char documents. Endpoint: https://mcp.gapup.io
- transcribe_chapterize_media - Transcription and chapterization of long-form media (YouTube, podcasts, direct audio/video) for content marketing teams, podcast publishers, edu tech, journalists and accessibility/compliance.

Pipeline:
• YouTube → timedtext captions (keyless) + oEmbed metadata + native timecode chapters from description
• Podcast RSS → episode description + duration + timecodes if embedded in show notes
• Direct media → partial (requires Whisper API via OPENAI_API_KEY + force_whisper:true)
• Chapters: native YouTube timecodes preferred; heuristic TF-IDF segmentation as fallback
• Summary: extractive TF-IDF top-sentences (no LLM required)
• Language detection: character-set heuristic (CJK→zh, kana→ja, hangul→ko, accents→fr/de/es)

Output formats: json (full structured object) | text (plain transcript) | srt | vtt

SLA: ≤15s budget total. Cache: 24h TTL. Endpoint: https://mcp.gapup.io
- seo_cro_audit - Full SEO + CRO audit of any public URL. Analyses technical SEO (HTTP status, HTTPS, title/meta/canonical/robots, H1-H2, JSON-LD structured data, sitemap, robots.txt, OG/Twitter cards), content SEO (word count, keyword density top-10, readability estimate, image alt coverage, internal/external links), performance signals (page size, estimated render time, inline scripts/styles, unoptimised images), and CRO (CTA detection, above-fold CTAs, forms, social proof, trust signals, pricing visibility). Optionally compares up to 5 competitor URLs. Returns 0-100 scores per dimension plus a prioritised (P0/P1/P2) recommendation list. ICP: marketing managers, SEO/CRO consultants, e-commerce ops, agency teams. Budget: 8s per URL. Cache TTL: 1h. Endpoint: https://mcp.gapup.io
- tool_recommend - Cross-tool recommendation system: given a free-text intent, returns the most appropriate tools from the 170+ Gapup MCP catalogue, ranked by confidence, with pre-filled input suggestions and an optimal multi-tool chain when applicable. Use this first when you are unsure which tool to call — it navigates the full catalogue for you. Supports 15+ static pre-designed chains for frequent intents (M&A due diligence, sanctions screening, ESG 360, AI Act compliance, FTO patent clearance, crypto wallet tracking, etc.). Domains: compliance | finance | intel | legal | content | data | trade | infra. Pure compute — $0.01/call, no external fetch. Ideal as a first call in any multi-step agent workflow. Endpoint: https://mcp.gapup.io
- crm_connector - Push, update, search and log activities in HubSpot, Salesforce or Pipedrive. 4 modes: push_lead (create contact/lead), update_opportunity (update deal stage/amount), search_contact (lookup by email), log_activity (call/email/meeting/note). Returns resource_id, direct CRM URL, signals and quality_score. If credentials are absent, returns a mock result with a warning signal. Auth: HubSpot via Bearer access_token; Salesforce via access_token + base_url; Pipedrive via api_key. Endpoint: https://mcp.gapup.io
- webhooks_manage - Manage HTTP webhook callbacks for async tools (T5/T6 batch flagships). Instead of polling every 5s, register a callback URL — Gapup posts the job result to your endpoint the moment it completes. Supported events: job.completed | job.failed | monitoring.alert | quota.threshold. Modes: register (add endpoint), list (view active webhooks), revoke (soft-delete), test (fire a test payload to verify your receiver), history (last 20 fires). Security: every delivery is signed with HMAC-SHA256 on the body — verify the X-Gapup-Signature header against sha256(secret, body). Endpoint: https://mcp.gapup.io

## Resources
- gapup://catalog/tools.json - Complete list of 143+ tools with tier, price (USDC), name, and description. Updated on server start. MIME type: application/json
- gapup://pricing/tiers.json - Full x402 pricing grid T0-T6 (commodity $0.002 → batch flagship $1.50) with per-tool breakdown. MIME type: application/json
- gapup://sanctions/ofac/latest - Latest OFAC Specially Designated Nationals list metadata — version, fetch date, entry count, checksum. Refreshed weekly. MIME type: application/json
- gapup://sanctions/combined/meta - Aggregated metadata across 6+ sanctions sources (OFAC/UN/EU/UK_HMT/SECO_CH/OSFI_CA/AUSTRAC_AU): entry counts, versions, overlap matrix. MIME type: application/json
- gapup://metrics/last-24h - Anonymised server telemetry for the last 24 hours: total calls, error rate, average latency, top callers. MIME type: application/json
- gapup://metrics/by-tool - Per-tool breakdown: call count, error count, avg/p50/p95 latency for the last 24 hours. MIME type: application/json
- gapup://health/connectors - Health status of all external data connectors (Wikipedia, Yahoo Finance, EDGAR, court filings, patent, weather, …): last success timestamp, consecutive errors. MIME type: application/json
- gapup://health/gapup-hub - Circuit breaker state (CLOSED/OPEN/HALF_OPEN) per gapup-hub endpoint, with failure counts and last success/failure timestamps. MIME type: application/json
- gapup://cache/stats - Cache backend (redis|memory), hit/miss counters, size. Reflects REDIS_URL presence at server start. MIME type: application/json
- gapup://catalog/aliases.json - Map of canonical tool names to alternative keywords agents may use when searching the catalogue. Use to discover tools via synonyms. MIME type: application/json
- gapup://health/deep - Full structured health report: build, telemetry, cache, external connectors, memory, disk, PM2 uptime. overall: healthy|degraded|unhealthy. MIME type: application/json
- gapup://health/alerts-recent - Last 20 alerts fired by the health monitor (P0/P1/P2), with severity, rule, message, timestamps. MIME type: application/json
- gapup://jobs/{job_id}/progress - Ring buffer of the last 50 progress notifications for a given job_id. Replace {job_id} with the actual job identifier (e.g. gapup://jobs/cdd_1234567890_abc123/progress). Useful for agents that reconnect after a network interruption and need to recover the current state. Returns: job_id, tool, status, progress_event_count, latest_progress_pct, events[]. MIME type: application/json
- gapup://catalog/deprecations - Active deprecation notices for tools in the deprecated or sunset phase. Agents should check this resource before building integrations on tools that may be sunset soon. Returns: total, deprecated_count, sunset_count, items[] with days_until_sunset. MIME type: application/json
- gapup://ab-tests/active - List of active pricing A/B experiments (tool, variants, allocation_strategy, started_at). When an experiment is active on a tool, the effective price may differ from the static pricing grid. Results per variant available via gapup://ab-tests/{experiment_id}/results. MIME type: application/json
- gapup://status/uptime - Platform uptime report for the requested period (default 7d). Includes uptime_pct, incidents array, latency percentiles (p50/p95/p99), and per-service breakdown. Use ?period=24h|7d|30d|90d. MIME type: application/json
- gapup://catalog/intent-routing - Static mapping of intent patterns to recommended tools and pre-designed workflow chains. 15 pre-built chains covering the most frequent agent use cases: M&A due diligence, KYC/sanctions screening, ESG 360, AI Act compliance, FTO patent clearance, crypto wallet tracking, competitor intelligence, etc. Use tool_recommend for dynamic scoring of arbitrary intents. MIME type: application/json
- gapup://analytics/cohorts/last-90d - Cohort retention analysis for the last 90 days grouped by signup_week. Includes per-cohort: agent_count, retention buckets (D1/D7/D30/D60/D90/D180), calls per agent (median/p25/p75), revenue_usd, churn_rate, and LTV estimate. Admin-only resource. Use GET /api/v1/analytics/cohorts for parameterized queries. MIME type: application/json
- gapup://health/regressions/last-7d - Week-over-week performance regression analysis per tool. Compares current 7-day window vs prior 7-day baseline on three axes: p95 latency (P1 alert if >+20%), error rate (P0 alert if >+5pts), traffic/calls-per-day (P2 alert if <-30%). Report is cached and refreshed every hour. Returns: tools_evaluated, regressions[], current_stats[], baseline_stats[]. MIME type: application/json

## Prompts
- competitive_brief - Generate a board-ready competitive brief on a company using multi-source MCP tools (competitive_deep_dive, market_sizing, trend_watcher, competitor_intel). Arguments: company, competitors
- kyc_due_diligence - Run full KYC + corporate registry + court filings check on a company or individual (kyc_screener, corporate_registry_lookup, court_filings_multi, web_search_multilang). Arguments: target, jurisdictions
- ma_target_screen - Pipeline M&A target screening: financials + IP + litigation + ESG (ma_deal_screener, patent_landscape, court_filings_multi, supplier_esg_audit, due_diligence_dossier). Arguments: target_company, deal_size_eur
- ai_act_readiness - Full EU AI Act readiness assessment for an AI system (ai_governance_pilot or ai_governance_full_report_async, privacy_compliance_audit, sustainability_reporting_pilot for GPAI models). Arguments: system_description, risk_tier_hint
- country_market_entry - Market entry brief for a country: regulations + tenders + clinical/IP landscape if applicable (ftg_country_study, ftg_country_regulations, gov_procurement_multi, corporate_registry_lookup, market_entry_strategist). Arguments: country_iso, sector
- climate_risk_portfolio - Climate risk scoring for a portfolio of properties or assets (weather_climate_intel, carbon_roadmap, action_plan_esg, matrice_materialite). Arguments: locations, horizon_year
- research_meta_review - Systematic review meta-synthesis on a scientific question (sci_literature_search, patent_landscape, web_search_multilang). Arguments: research_question, domain
- compliance_full_audit - End-to-end compliance audit: GDPR + AI Act + ESRS + KYC + court filings (privacy_compliance_audit, ai_governance_pilot, esrs_narrative_builder, kyc_screener, court_filings_multi, matrice_materialite). Arguments: company

## Metadata
- Owner: io.github.getgapup
- Version: 0.2.0
- Runtime: Streamable Http
- Transports: HTTP
- License: Not captured
- Language: Not captured
- Stars: Not captured
- Updated: May 18, 2026
- Source: https://registry.modelcontextprotocol.io