# Raven MCP server Design intelligence for coding agents: audits, design systems, and a taste profile agents consult. ## Links - Registry page: https://www.getdrio.com/mcp/ai-ravenmcp-raven-mcp - Repository: https://github.com/rhinocap/raven-mcp - Website: https://ravenmcp.ai ## Install - Command: `npx -y raven-mcp` - Endpoint: https://mcp.ravenmcp.ai/api/mcp - Auth: Not captured ## Setup notes - Package: Npm raven-mcp v2.3.0 - Remote endpoint: https://mcp.ravenmcp.ai/api/mcp ## Tools - get_principles - Get design principles relevant to a UI context. Returns usability heuristics, laws of UX, Gestalt principles, accessibility requirements, typography rules, and color theory — matched to what you're designing. Endpoint: https://mcp.ravenmcp.ai/api/mcp - get_pattern - Get proven UI/UX patterns for a specific design type. Returns do's, don'ts, evidence, and checklists for signup flows, pricing pages, navigation, forms, landing pages, dashboards, modals, empty states, error states, loading states, CTAs, social proof, and mobile conversion. Endpoint: https://mcp.ravenmcp.ai/api/mcp - get_business_strategy - Get business and monetization strategies for digital products. Covers monetization models, retention strategies, onboarding optimization, growth mechanics, and product metrics frameworks. Endpoint: https://mcp.ravenmcp.ai/api/mcp - evaluate_design - Evaluate a design description against UX principles. Returns relevant principles, potential violations, and improvement suggestions. Endpoint: https://mcp.ravenmcp.ai/api/mcp - search_knowledge - Search across all design principles, UI patterns, and business strategies. Use when you need to find specific guidance or don't know which category to look in. Endpoint: https://mcp.ravenmcp.ai/api/mcp - get_checklist - Get a pre-publish checklist for a specific UI type. Returns actionable yes/no items to verify before shipping. Endpoint: https://mcp.ravenmcp.ai/api/mcp - get_d4d_framework - Get the Design for Delight (D4D) framework templates. Returns customer problem statement, ideal state, hypothesis, LOFA, and experiment templates for structured product thinking. Endpoint: https://mcp.ravenmcp.ai/api/mcp - list_design_systems - Browse available design systems for tokens. Filter by category (fintech, productivity, developer, component-library, design-system) or search by name. Endpoint: https://mcp.ravenmcp.ai/api/mcp - get_design_system - Get design tokens for a specific design system. Returns colors, typography, spacing, radii, elevation, and motion tokens in W3C DTCG, CSS custom properties, or flat format. Endpoint: https://mcp.ravenmcp.ai/api/mcp - compose_system - Mix tokens from different design systems to create a custom composite. Example: Linear's colors + Stripe's typography. Endpoint: https://mcp.ravenmcp.ai/api/mcp - audit_page - Audit HTML/CSS against Raven's design quality standards. Checks typography (min 13px, weight 400+, modular-scale heading ratios, line-height consistency), accessibility (WCAG touch targets, alt text, contrast), responsive patterns (flexbox over grid, clamp sizing, max-width containers), style guide compliance (CSS custom properties, no bare hex), and visual rhythm (4/8px spacing grid, tight spacing scale, palette size). Pass containerMaxWidth (your design system's canonical container token, in px) to make the max-width check token-aware — it then flags containers that diverge from your system (too narrow OR too wide) instead of a generic 1200px heuristic. Returns pass/fail per check with specific fix instructions. Endpoint: https://mcp.ravenmcp.ai/api/mcp - score_page - Score an HTML/CSS page across 7 design categories (Structure, Typography, Color & palette, Spacing & rhythm, Accessibility, Responsive layout, Design tokens), each rated 0–10. Scores are derived deterministically from the same checks as audit_page — no browser required. Pass html directly, or pass url to have Raven launch headless chromium, render the page, and score the RENDERED DOM. Also returns the same overall 0–100 score and A–D grade audit_page produces, the weakest category, and the three categories Raven does not mechanically assess (brand, conversion, motion) with guidance on which tools to use for those. Endpoint: https://mcp.ravenmcp.ai/api/mcp - audit_parity - Compare iOS vs Android element snapshots against a checklist of named spatial relationships (vertical centering, baseline/left alignment, equal gap/size, presence, truncation) and flag per-relation match/mismatch/uncertain — catches cross-platform layout drift like status text centered on one platform but top-aligned on the other. Provide ios+android {elements,viewport} snapshots and a checklist[]. Endpoint: https://mcp.ravenmcp.ai/api/mcp - audit_ios_a11y - Score an accessibility-enriched iOS element snapshot — missing accessibilityLabel/value/traits, sub-44pt tap targets, per-text WCAG contrast, Dynamic Type clipping, and VoiceOver reading order. Provide {elements:[{label,value,hint,traits,role,rect,fontPt,fgColor,bgColor,dynamicTypeClipped}],viewport}. Capture via the AccessibilitySnapshot XCUITest / ios-capture harness. Endpoint: https://mcp.ravenmcp.ai/api/mcp - audit_responsive_visibility - Render a URL at multiple breakpoints and flag content elements that are visible on desktop but hidden on mobile (display:none / opacity:0 / visibility:hidden / zero-size). Categorises each flag as 'likely-oversight' (content that vanishes on mobile — the hidden-on-mobile content bug) vs 'intentional' (decorative). Returns a table of selector / hiding-class / mobile-visible / desktop-visible / category. Requires headless chromium. Endpoint: https://mcp.ravenmcp.ai/api/mcp - audit_contrast - Compute WCAG contrast ratios for every text element on a rendered page (pass url) or from a supplied dom_snapshot. Reports AA (4.5:1 normal, 3:1 large) and AAA pass/fail per element and surfaces failing pairs with selector, ratio, and delta-to-pass — replacing manual eyedropper + ratio math. Endpoint: https://mcp.ravenmcp.ai/api/mcp - suggest_contrast_fix - Given failing WCAG color pairs, return the MINIMAL color change that clears the target ratio. For each {fg,bg} pair, computes the smallest foreground adjustment (and an alternative background adjustment) that reaches AA/AAA — with the achieved ratio and direction. Feeds directly from audit_contrast's failing pairs: pass them here to get concrete passing values instead of brute-forcing colors by hand. Pure offline math. Endpoint: https://mcp.ravenmcp.ai/api/mcp - audit_url - Layer 0 render-and-capture audit: renders a LIVE URL at each viewport×theme, scroll-settles (fires whileInView/IntersectionObserver reveals; plays preload=none videos), fires hover/click/focus interactions, and captures real pixels + the rendered DOM. Then runs the existing audit_page rule engine, per-element WCAG contrast, responsive-visibility (desktop-shown/mobile-hidden), blank-media detection, sliced-image edge symmetry, and hover-state white-wash detection over the captures. Every finding is tagged confirmed | likely-artifact | inconclusive with its evidence, ranked by severity. This is the tool that catches real-world visual nits invisible to HTML-string/geometry audits: cropped images, blank videos, hover white-wash, sliced exports, and hidden-on-mobile content. Requires headless chromium. Endpoint: https://mcp.ravenmcp.ai/api/mcp - audit_content - Evaluate an array of content items (headings, prose, CTAs, labels, captions, metrics, outcomes) against UX-writing principles and deterministic heuristics. Returns a per-item verdict (pass/warn/fail) with matched principle ids, concrete issues grounded in principle text, a before→after rewrite suggestion, and an aggregate summary. Heuristics: metric items must carry a number+unit; cta/label must be action-led and ≤4 words; prose flags passive voice, jargon, and hedging; headings flag filler openers and buzzwords; captions flag duplication of any heading in the batch. Pure offline — no network or browser. Use this instead of evaluate_design when you need per-item content verdicts rather than the principle library. Endpoint: https://mcp.ravenmcp.ai/api/mcp - audit_typography - Audit the typographic SCALE of a rendered page (pass url) or a pre-collected snapshot of text nodes. Emits a focused report: (a) MODULAR SCALE — detects the dominant ratio (~1.2/1.25/1.333/1.5) across distinct font sizes and flags off-scale outliers; (b) LINE-HEIGHT CONSISTENCY — unitless lh/fs ratio per node, identifies the body rhythm and flags outliers; (c) WEIGHT LADDER — distinct weights, flags >4 weights or non-standard CSS values. Returns scale, line_height, weight_ladder, nodes_analyzed, and findings[{rule,severity,selector,message,fix}]. Goes beyond audit_page's pass/fail typography checks. url mode requires headless chromium. Endpoint: https://mcp.ravenmcp.ai/api/mcp - audit_tap_targets - WCAG 2.5.5 / Apple 44pt tap-target audit for the web. Collects every interactive element (a, button, [role=button], input[type=submit/button/checkbox/radio], select, summary, label[for], [onclick], [tabindex>=0]) and emits a PER-ELEMENT fix table for any whose rendered width or height is below the minimum (default 44px): selector, role, visible text, measured w/h, pixel deficit per axis, and a concrete CSS fix. Sorted worst-first. Two modes: pass url (renders in headless chromium, measures real getBoundingClientRect) or pass elements[] snapshot (pure, no browser). Endpoint: https://mcp.ravenmcp.ai/api/mcp - get_brand_system - Get a complete design system for building an app with branding like a specific company. Say 'Make me an app with branding like Spotify' and get the full token set, style guide, and implementation instructions. Matches against 12 known design systems and provides closest match with ready-to-use CSS. Endpoint: https://mcp.ravenmcp.ai/api/mcp - generate_design_system - Generate a complete, custom design system with full token set. Provide a brand color to auto-generate a harmonious palette, pick a style preset, and export as visual HTML documentation, CSS variables, W3C DTCG JSON, Figma Variables, or SVG palette card. The HTML export is a beautiful, self-contained page suitable for sharing with stakeholders. Endpoint: https://mcp.ravenmcp.ai/api/mcp - audit_layout - Evaluate visual rhythm from a rendered page's geometry. Call with no arguments to get a DevTools snippet to paste into your page — it prints {elements, viewport} JSON. Call again with that JSON to get alignment, gap-rhythm, and optical-balance scores. This is the complement to audit_page for things only visible once rendered. Endpoint: https://mcp.ravenmcp.ai/api/mcp - audit_swiftui - Audit SwiftUI source against Apple's Human Interface Guidelines. Flags hardcoded .font(.system(size:)) below ~13pt and tiny semantic fonts (.caption/.caption2), hardcoded Color(red:green:blue:)/hex instead of asset-catalog or semantic system colors, an empty/undefined AccentColor, interactive frames below 44×44pt, and ad-hoc spacing off the 4/8-pt grid. Rewards semantic Dynamic Type fonts, semantic system colors, SF Symbols, and flexible frames. iOS-native checks only — no web/CSS rules. Returns pass/fail per check with fix instructions. Endpoint: https://mcp.ravenmcp.ai/api/mcp - audit_screen - Audit a rendered mobile screen (iOS or Android) from a view-hierarchy/accessibility snapshot. Call with no arguments for the expected snapshot shape and how to capture it. Pass platform:"android" to score against the 48dp Material touch minimum and Material muted roles (onSurfaceVariant/outline = warn not fail); default platform:"ios" scores 44pt and treats secondaryLabel/tertiaryLabel as platform-standard. Both score touch targets, contrast, and visual rhythm (alignment, gap consistency, optical balance). Same return shape as audit_page. Endpoint: https://mcp.ravenmcp.ai/api/mcp - audit_ios_screen - Audit a rendered iOS screen from a view-hierarchy/accessibility snapshot (and optional screenshot). Alias of audit_screen with platform:"ios". Call with no arguments for the expected snapshot shape. Call with {elements:[{label,rect:{x,y,w,h},role,fontPt,fgColor,bgColor}],viewport:{w,h}} to score 44×44pt touch targets, contrast (with iOS secondaryLabel/tertiaryLabel treated as platform-standard — warn not fail), and visual rhythm (alignment, gap consistency, optical balance) in points. Same return shape as audit_page. Endpoint: https://mcp.ravenmcp.ai/api/mcp - audit_ios_privacy - Audit an iOS or React Native/Expo app's privacy posture for App Review and user trust. Reads a native Info.plist XML OR an Expo app.json (managed Expo apps have no Info.plist) — plus optional PRIVACY.md, entitlements, and source. Flags: NS*UsageDescription strings that are vague/missing or contradict the code (e.g. a HealthKit write claim the code never fulfills), entitlements/permissions and Android permissions the app doesn't use, ATS cleartext exceptions and non-HTTPS endpoints, secrets/keys shipped in the bundle or app.json, and default data-egress paths not disclosed at the point of choice (a pre-selected 'Recommended' option that silently sends personal data to a server). Same return shape as audit_page. Endpoint: https://mcp.ravenmcp.ai/api/mcp - audit_rn - Audit React Native / Expo source (JSX/TSX + StyleSheet) against the iOS HIG + Android Material conventions RN must satisfy. Flags touchables missing accessibilityLabel/accessibilityRole, touchables below 44pt without hitSlop, allowFontScaling={false}, fontSize below ~13, screens without SafeAreaView, and (for multi-mode apps) hardcoded colors with no useColorScheme/Appearance dark-mode handling. Rewards SafeAreaView, hitSlop, Platform-aware code, and a theme. RN-native checks only — no web/CSS or SwiftUI rules. Same return shape as audit_page. (RN renders to native widgets, so audit_ios_screen scores the rendered screen.) Endpoint: https://mcp.ravenmcp.ai/api/mcp - list_content_systems - Browse available content design systems — brand voice and tone guides (Conversational Product Voice, GOV.UK, Shopify Polaris, Atlassian). Filter by category or search by name. Endpoint: https://mcp.ravenmcp.ai/api/mcp - get_content_system - Get a brand's content design system — voice attributes, tone shifts by context, vocabulary (use/avoid/never), grammar rules, content patterns for errors/empty-states/buttons/etc., and inclusive language guidance. Endpoint: https://mcp.ravenmcp.ai/api/mcp - get_content_principles - Get UX-writing principles — clarity over cleverness, active voice, error-message anatomy, inclusive language, voice vs tone, and more. Filter by the writing context (e.g. 'error messages', 'notifications', 'form labels'). Endpoint: https://mcp.ravenmcp.ai/api/mcp - get_content_pattern - Get content design patterns — copy recipes for error messages, empty-state copy, notifications, and form validation. Returns do's, don'ts, good/bad examples, evidence, and a checklist. Endpoint: https://mcp.ravenmcp.ai/api/mcp - get_research_method - Get research method details — qualitative (interviews, contextual inquiry, diary, field, intercept), quantitative (surveys, analytics, A/B tests, benchmarking, clickstream), or usability (moderated, unmoderated, 5-second, card sort, tree test, heuristic eval). Returns specific protocols, do/don't guidance, evidence, and a checklist. Use when the user is designing a study or asking how to measure something. Endpoint: https://mcp.ravenmcp.ai/api/mcp - get_metrics_framework - Get a product-metrics framework — HEART (Google), AARRR/Pirate (Dave McClure), North Star Metric, Conversion Funnel, RICE Scoring, or OKRs. Returns structure, when-to-use, pitfalls, and examples. Use when the user asks 'how should we measure success?' or 'what metrics should we track?' Endpoint: https://mcp.ravenmcp.ai/api/mcp - get_service_pattern - Get a service design pattern — service blueprinting, human handoff, signup-as-service, omnichannel continuity, or moments of truth / recovery. Returns patterns, do/don't guidance, evidence, and a checklist. Use when the user is designing a service flow, escalation, cross-channel experience, or moment of truth. Endpoint: https://mcp.ravenmcp.ai/api/mcp - get_service_standard - Get the GOV.UK Service Standard — 14 points the UK government uses to assess whether a public service is ready to launch. Widely applicable as a rigorous service-quality checklist beyond government. Use when the user asks how to evaluate a whole service. Endpoint: https://mcp.ravenmcp.ai/api/mcp - generate_service_blueprint - Render a service blueprint as a self-contained HTML page. Supports two modes: (1) classic Shostack single-actor blueprint — user action, frontstage, backstage, support, evidence, pain/delight; (2) two-actor HI-loop blueprint — when `actors` is supplied, renders two swim lanes with a line of interaction between them (e.g. customer ↔ lawyer, patient ↔ doctor, buyer ↔ agent). Each actor gets their own actions, frontstage (what they see), and evidence. Optionally accepts an ideal-state to render side-by-side with the current state. Endpoint: https://mcp.ravenmcp.ai/api/mcp - get_brand_principles - Get brand and visual-design principles — logo usage (clear space, min sizes, variants, placement, restraint), gradient usage (hierarchy, palette, contrast, trend vs signature), imagery (consistency, representation, purpose), visual hierarchy, and brand-as-system thinking. Use when the user asks about branding, logos, gradients, imagery, visual consistency, or how to treat a brand across surfaces. Endpoint: https://mcp.ravenmcp.ai/api/mcp - get_brand_trends - Get current brand and visual-design trends — what's working in 2026 and where each trend fits or fails. Includes bento grids, monospace type, neon-on-dark-glass, generative patterns, brutalism rebound, AI-generated imagery, lowercase/mixed case. Each trend is time-stamped — treat as a calibration signal, not a prescription. Endpoint: https://mcp.ravenmcp.ai/api/mcp - list_creative_models - Browse Raven's provider-agnostic creative model catalog. These are capability slots for image, video, 3D, audio, character consistency, and creative analysis. Use a configured RAVEN_CREATIVE_RUNNER to route jobs to any local CLI or API wrapper. Endpoint: https://mcp.ravenmcp.ai/api/mcp - list_creative_presets - Browse Raven creative presets for product photoshoots, marketplace cards, UGC ads, TV spots, cinematic reveals, social launch packs, storyboards, and infographics. Endpoint: https://mcp.ravenmcp.ai/api/mcp - score_creative - Score a creative prompt, script, or ad concept for hook strength, benefit clarity, product signal, call-to-action, channel fit, audience fit, and brand fit. This is a transparent heuristic, not a proprietary prediction model. Endpoint: https://mcp.ravenmcp.ai/api/mcp - audit_consistency - Audit multiple pages for cross-page consistency of content-container width and hero heading tier. Pass ≥2 pages ({name, html}) collected from different routes on the same site. Infers the canonical (modal) value from the corpus when no token is supplied, so you need not know the project's design token in advance. Flags the issue #9 single-blob blind spot: pages that each pass audit_page but silently disagree with each other on container width or hero size class. Returns per-page extraction (container_px, container_classes, hero_classes, signatures), consistency dimensions with reference values, outlier page names, issues[], score (100/50/0 → A/C/D), and a plain-text summary. Pure offline — no browser, no network. Endpoint: https://mcp.ravenmcp.ai/api/mcp - audit_video_playback - Render a page in headless Chromium and observe whether each