# AI Business System Advisor MCP server

Find the safest first AI workflow before investing in AI agents or automation.

## Links
- Registry page: https://www.getdrio.com/mcp/io-github-tenkai2018-ai-business-system-advisor-mcp
- Repository: https://github.com/tenkai2018/ai-business-system-advisor-mcp

## Install
- Command: `npx -y ai-business-system-advisor-mcp`
- Endpoint: https://mcp.prodxsolution.com/ai-business-system-advisor/mcp
- Auth: Not captured

## Setup notes
- Package: Npm ai-business-system-advisor-mcp v0.1.9
- Remote endpoint: https://mcp.prodxsolution.com/ai-business-system-advisor/mcp

## Tools
- analyze_business_context (Analyze Business Context) - Summarizes the supplied business context, including customer, offer, workflow, goals, constraints, readiness signals, missing information, and confidence. Endpoint: https://mcp.prodxsolution.com/ai-business-system-advisor/mcp
- map_customer_touchpoints (Map Customer Touchpoints) - Maps customer-facing workflow stages, trust-sensitive moments, automation-safe areas, human-critical areas, missing information, and confidence. Endpoint: https://mcp.prodxsolution.com/ai-business-system-advisor/mcp
- identify_bottlenecks (Identify Bottlenecks) - Identifies likely revenue, operations, customer experience, and trust/control bottlenecks from the supplied business context and returns a public-safe summary. Endpoint: https://mcp.prodxsolution.com/ai-business-system-advisor/mcp
- evaluate_ai_opportunities (Evaluate AI Opportunities) - Evaluates candidate AI workflow ideas for business value, implementation readiness, repeatability, trust/control risk, warnings, and missing information. Endpoint: https://mcp.prodxsolution.com/ai-business-system-advisor/mcp
- assess_trust_control_risks (Assess Trust And Control Risks) - Reviews a proposed AI workflow for human review needs, data boundaries, quality controls, escalation triggers, unsafe automation risks, and confidence. Endpoint: https://mcp.prodxsolution.com/ai-business-system-advisor/mcp
- recommend_first_workflow (Recommend First Workflow) - Recommends the safest narrow AI-human workflow to implement first, including roles, review rules, escalation rules, success metrics, and missing information. Endpoint: https://mcp.prodxsolution.com/ai-business-system-advisor/mcp
- generate_mini_report (Generate Mini Report) - Generates a public-safe mini business system review with snapshot, bottlenecks, opportunities, risks, first workflow, next step, missing information, and confidence. Endpoint: https://mcp.prodxsolution.com/ai-business-system-advisor/mcp
- recommend_next_step (Recommend Next Step) - Recommends a practical next-step category based on business goal, workflow complexity, implementation readiness, risk level, preferences, and missing information. Endpoint: https://mcp.prodxsolution.com/ai-business-system-advisor/mcp
- export_intake_packet (Export Intake Packet) - Creates a structured public-safe markdown and JSON intake packet with business context, findings, risks, recommended workflow, missing information, and confidence. Endpoint: https://mcp.prodxsolution.com/ai-business-system-advisor/mcp

## Resources
- advisor://overview - Overview Overview MIME type: text/markdown
- advisor://how-it-works - How it works How it works MIME type: text/markdown
- advisor://readiness-guide - Readiness guide Readiness guide MIME type: text/markdown
- advisor://sample-mini-report - Sample mini report Sample mini report MIME type: text/markdown
- advisor://sample-intake-packet - Sample intake packet Sample intake packet MIME type: text/markdown
- advisor://privacy - Privacy note Privacy note MIME type: text/markdown

## Prompts
- run_mini_business_system_review - Run mini business system review Guide the assistant to run a public-safe mini business system review. Arguments: businessContext
- evaluate_ai_workflow_idea - Evaluate AI workflow idea Evaluate whether an AI workflow idea is safe, useful, and reviewable. Arguments: idea
- prepare_diagnostic_intake - Prepare diagnostic intake Prepare a structured intake packet for a deeper business-system review. Arguments: notes
- governance_gap_snapshot - Governance gap snapshot Identify data boundaries, review rules, escalation rules, and quality controls. Arguments: workflow

## Metadata
- Owner: io.github.tenkai2018
- Version: 0.1.9
- Runtime: Npm
- Transports: STDIO, HTTP
- License: Not captured
- Language: Not captured
- Stars: Not captured
- Updated: May 31, 2026
- Source: https://registry.modelcontextprotocol.io