` in the rendered DOM)\n- `likely-artifact` — the finding is an artifact of the static audit method (e.g. a `<video preload=\"none\">` rendered blank, which is expected behavior, not a missing resource)\n- `inconclusive` — the finding cannot be independently verified (e.g. aggregate rules like color-palette size)\n\nThe result includes `adversarial_verification: { debunked_count, confirmed_count, inconclusive_count }`, where debunked_count is the number of likely-artifacts. This surfaces false positives so you only fix real issues. Backwards-compatible: when `adversarial_verify` is absent or false, the output is identical to prior versions.\n\n**Setup:** First time only, run `npx playwright install chromium` to download the browser binary. If the binary is missing when you call audit_page with `url`, you'll see a clear instruction to run the install command.\n\n## Before/after design diffs\n\n`evaluate_design` can now accept base64-encoded PNG screenshots to measure whether a fix actually changed the rendered output.\n\n**Usage:**\n- Pass `before_screenshot` and `after_screenshot` (both base64 PNGs, with or without the `data:image/png;base64,` prefix).\n- Raven returns `fix_confirmed: true` if the images differ by > 0.1% of pixels (accounting for jpeg/PNG decode variance).\n- `changed_ratio` — exact fraction of pixels that changed (0–1).\n- `changed_region` — bounding box `{ x, y, w, h }` of the changed pixels (null if no changes detected).\n- `dimensions` — image-derived measurements (canvas size, brightness, color shift) as context, with the caveat that these are pixel-level proxies, not Raven principle scores.\n\nWhen before/after screenshots are provided alongside a `description`, `evaluate_design` returns both the principle-based evaluation and the pixel diff. When screenshots are provided without a description, the evaluation gracefully skips the principle search and returns the diff only. Backwards-compatible: without screenshots, the tool behaves identically to prior versions.\n\n## Release updates\n\nRaven ships new principles, patterns, and brand systems regularly. For one email per minor/major release (patches stay quiet):\n\n- **Web:** [ravenmcp.ai/#updates](https://ravenmcp.ai/#updates) — 10 seconds, one email field.\n- **In-product:** ask Claude *\"register me for Raven updates at you@work.com\"* — Claude calls `raven_register` and you're in.\n\nNo marketing, unsubscribe anytime. Powered by Resend.\n\n## Start every project calibrated\n\nTaste is per-surface: the same designer wants monochrome one-accent rules enforced on their portfolio and *none* of them on a product site, with a slightly different voice on each. The Taste Engine handles this with a **kickoff interview** (once per project — every question skippable, most with plain-language multiple-choice options, from navigation pattern to aesthetic family to specialty libraries) whose answers persist as a surface binding that every future audit applies automatically. And when generated work misses, `mode:'refine'` turns that dissatisfaction into a re-interview against the stored binding instead of a dead end.\n\nRaven ships this flow in its MCP server instructions, so agents that honor server instructions (Claude Code, Claude Desktop) run the interview at project kickoff on their own: `get_taste_interview` → ask the user → `bind_taste_surface` → done. If your client doesn't surface server instructions — or you want the ritual to be non-negotiable — add one line to the project's `CLAUDE.md` / `AGENTS.md`:\n\n```markdown\nBefore the first design/UI/copy work in this repo, run Raven's get_taste_interview\n(profile <name>, project <repo-name>); if existing_binding is null, ask me its\nquestions and persist with bind_taste_surface. Pass project:'<repo-name>' on every\naudit_taste after that.\n```\n\nAlready-calibrated projects cost one cheap call (`existing_binding` comes back non-null and the agent proceeds). Uncalibrated audits still work — scoped rules just demote to warn and the result carries a `calibration_hint` — so calibration is never a wall, only a sharpener.\n\n## Learning loop\n\nRaven keeps a small **local-only** log of how you use it so you (and Claude) can spot which patterns you build most often and which gaps show up again and again.\n\n- **Location:** `~/.raven/usage.jsonl` (override with `RAVEN_USAGE_LOG=/path`).\n- **What's written:** tool name, timestamp, elapsed ms, and a tiny insight object — audit score/warning rule names, pattern `type`, brand company name, search layer. **Never the HTML you audit, never prompt text, never brand copy.**\n- **What's never written:** raw page bodies, client content, your work product.\n- **Disable entirely:** `RAVEN_NO_USAGE_LOG=1`.\n- **Reflect:** ask Claude *\"what have I been using Raven for?\"* and it will call `raven_reflect`, which reads the log locally and summarizes the last N days — most-used tools, recurring audit warnings (likely knowledge gaps), patterns you request most, design systems you reach for.\n\nNothing is sent to a remote server. If a recurring gap is worth turning into a new Raven principle or pattern, you file an issue by hand — the automated pipeline at [github.com/rhinocap/raven-mcp](https://github.com/rhinocap/raven-mcp) handles it from there.\n\n## Development\n\n```bash\nnpm run dev # Run with tsx (hot reload)\nnpm run build # Compile TypeScript\nnpm start # Run compiled output\n```\n\n## License & attribution\n\nRaven MCP is released under the [MIT License](https://github.com/rhinocap/raven-mcp/blob/main/LICENSE) — Copyright (c) 2026 Andrew Cunliffe.\n\nIf you fork, embed, or redistribute Raven (in whole or in part), retain the MIT license notice and the `LICENSE` file. If you ship Raven inside another product, include attribution to \"Raven MCP — https://ravenmcp.ai\" in your acknowledgements.\n\nRaven's knowledge base paraphrases and references work from many third-party sources — Nielsen Norman Group, Laws of UX (CC BY-NC-ND 4.0), Gestalt principles, WCAG (W3C), Mailchimp (CC BY-NC 4.0), GOV.UK (Open Government Licence v3.0), Shopify Polaris, Atlassian Design, and others. Each entry carries a `sources` URL field. See [NOTICE](https://github.com/rhinocap/raven-mcp/blob/main/NOTICE) for the full list of upstream sources and license terms; some carry their own conditions beyond MIT.\n\nThis is a personal project. It is not endorsed by Intuit Inc. or any other company referenced in its source data.\n\n## Data structure\n\nAll knowledge lives in `src/data/` as static JSON files:\n\n```\nsrc/data/\n principles/ # Nielsen, Laws of UX, Gestalt, accessibility, typography, color, mobile, D4D\n patterns/ # signup, pricing, nav, forms, landing, dashboard, modals, empty/error/loading, CTA, social proof, mobile\n business/ # monetization, retention, onboarding, growth, metrics\n tokens/ # registry.json + systems/ (stripe, linear, vercel, …)\n content/ # voice & tone: Mailchimp, GOV.UK, Shopify Polaris, Atlassian\n systems/ # registry.json + brand-voice JSONs (Mailchimp, GOV.UK, Polaris, Atlassian)\n principles/ # UX-writing principles (clarity, active voice, error anatomy, …)\n patterns/ # copy recipes for errors, empty states, notifications, form validation\n research/ # study protocols + metrics frameworks\n principles/ # research fundamentals (method match, bias, sample size, ethics, triangulation, …)\n methods/ # qualitative, quantitative, usability\n frameworks/ # HEART, AARRR, North Star, conversion funnel, RICE, OKRs\n service-design/ # service-level principles + patterns + frameworks\n principles/ # Stickdorn, Shostack, peak-end, moments of truth, handoff\n patterns/ # service blueprinting, human handoff, signup-as-service, omnichannel, moments of truth\n frameworks/ # GOV.UK Service Standard (14 points)\n brand/ # brand & visual design\n principles/ # logo, gradient, imagery, hierarchy, brand-as-system\n trends/ # 2026-current.json\n```\n","changelogMarkdown","videoKey","requiredSecretsJson","publishedAt","priceCents","trialDays",0,"categoryDisplayName","Integrations","upstream",{"_94":95,"_96":97,"_98":99,"_100":101,"_102":103},"requiredSecrets",[],"tags",[],"assets",[],"stats",{"_92":79,"_93":79},"ratingAvg","reviewCount","topics",[],"license","MIT","language","HTML","registryName","ai.ravenmcp/raven-mcp","homepage","https://ravenmcp.ai","ENV",{"_106":107,"_108":109,"_110":111},"ENVIRONMENT","production","TURNSTILE_SITE_KEY","0x4AAAAAAB8-rEI2gNDf_QhU","SENTRY_DSN","https://45fd1229f78089d5c3ee78be128030e1@o4510583261757440.ingest.de.sentry.io/4510584253448272"] </article></body></html>

[{"_1":2,"_3":-5,"_4":-5},"loaderData",{"_5":6,"_7":8,"_9":10},"actionData","errors","root",{"_104":105},"routes/modules.$creator.$moduleId",{"_14":15,"_16":17,"_18":19,"_20":21},"routes/modules.$creator.$moduleId.endpoints",{"_11":12,"_13":-5},"error","Module not found","tools","module",{"_20":22,"_23":24,"_25":26,"_27":28,"_29":30,"_31":32,"_33":26,"_34":-5,"_35":36,"_37":-5,"_38":-5,"_39":-5,"_40":41,"_42":43,"_44":45,"_46":45,"_47":48,"_49":50,"_51":52,"_53":-5,"_54":45,"_55":56,"_57":58,"_59":-5,"_60":-5,"_61":-5,"_62":-5,"_63":64,"_65":66,"_67":68,"_69":70,"_71":72,"_73":-5,"_74":-5,"_75":-5,"_76":45,"_77":-5,"_78":79,"_80":81,"_82":83,"_84":85,"_86":87,"_88":89,"_90":91},"apiUrl","https://odel.app/api","creator","rhinocap","moduleId","raven-mcp","@rhinocap/raven-mcp","displayName","Raven","tagline","Design intelligence for AI-generated UI — principles, patterns, content, brand, design tokens.","iconKey","https://avatars.githubusercontent.com/u/20427572?v=4","category","integrations","status","published","metaDescription","metaKeywords","deploymentType","external","workerName","bindingName","mcpConfig","pricingModel","free","creatorUserId","system:external-import","createdAt",1783311704000,"updatedAt","sourceRegistry","official-mcp-registry","sourceUrl","https://registry.modelcontextprotocol.io/v0/servers?search=ai.ravenmcp%2Fraven-mcp","sourceVerified",false,"sourceMissingSince","importedAt","upstreamStars",2,"upstreamUpdatedAt",1783310048000,"detectedTransport","detectedAuthType","probeStatus","lastProbedAt","githubRepoUrl","https://github.com/rhinocap/raven-mcp","githubRepoFullName","rhinocap/raven-mcp","releaseId","ext-rhinocap-raven-mcp","version","1.3.3","descriptionMarkdown","# Raven MCP\n\n**Odin's ravens brought back knowledge of the world — Raven brings back design intelligence.**\n\nA design knowledge MCP server that Claude can query when generating UI. Eight layers: principles, patterns, content design systems, research methods, service design, brand/visual, business strategy, and design tokens.\n\n> Raven MCP is a personal open-source project by [Andrew Cunliffe](https://ravenmcp.ai). It is **not endorsed by, affiliated with, or supported by Intuit Inc.** or any other company referenced in its source data. See [NOTICE](https://github.com/rhinocap/raven-mcp/blob/main/NOTICE) for full attribution of upstream sources and their licenses.\n\n## What it does\n\nRaven gives Claude access to a comprehensive design knowledge base:\n\n- **Principles** — Nielsen's 10 Heuristics, all 21 Laws of UX, Gestalt principles, WCAG accessibility, typography rules, color theory, mobile UX, D4D framework, UX writing, service design, brand, color-systems (palette-size discipline), and spacing-systems (base-unit grid + scale limits)\n- **Patterns** — Proven UI patterns for signup flows, pricing pages, navigation, dropdown/select menus, forms, landing pages, dashboards, modals, empty/error/loading states, CTAs, social proof, mobile conversion — plus content patterns (error messages, empty-state copy, notifications, form validation) and service patterns (service blueprinting, human handoff, signup-as-service, omnichannel continuity, moments of truth)\n- **Content systems** — Voice & tone guides from publicly documented brand systems: Mailchimp, GOV.UK, Shopify Polaris, and Atlassian\n- **Research** — Qualitative, quantitative, and usability methods with do/don't protocols and checklists. Metrics frameworks: HEART, AARRR/Pirate, North Star Metric, conversion funnel, RICE, OKRs.\n- **Service design** — Service blueprinting (with HTML blueprint generation — current vs. ideal state), human-handoff patterns, signup-as-service, omnichannel continuity, moments of truth / recovery, and the GOV.UK Service Standard\n- **Brand & visual** — Logo usage (clear space, min sizes, variants, placement, restraint), gradient usage (hierarchy, palette, contrast, trend vs signature), imagery (consistency, representation, purpose), visual hierarchy, brand-as-system, and current (2026) visual-design trends\n- **Business** — Monetization models, retention strategies, onboarding optimization, growth mechanics, and product metrics frameworks\n- **Tokens** — Design system tokens for Stripe, Linear, and more\n- **Creative studio** — Local-first brand profiles, asset references, character reference profiles, provider-agnostic image/video/3D/audio generation jobs, campaign plans, and transparent creative scoring. Raven does not ship media-provider credentials; set `RAVEN_CREATIVE_RUNNER` to route jobs to your own renderer.\n\n## Install\n\n### Claude Code — one command\n```bash\nclaude mcp add raven -- npx -y raven-mcp\n```\n\n### Manual config (Claude Desktop or team `.mcp.json`)\n```json\n{\n \"mcpServers\": {\n \"raven\": {\n \"command\": \"npx\",\n \"args\": [\"-y\", \"raven-mcp\"]\n }\n }\n}\n```\n\n### Claude Desktop — one-click extension\nPrefer not to edit JSON? Download [raven.mcpb](https://ravenmcp.ai/raven.mcpb) and double-click it. Claude Desktop installs Raven automatically — no Node, no terminal.\n\n### From source\n```bash\ngit clone https://github.com/rhinocap/raven-mcp.git\ncd raven-mcp && npm install && npm run build\n```\n\n## Tools\n\n| Tool | Description |\n|------|-------------|\n| `get_principles` | Get design principles relevant to a UI context |\n| `get_pattern` | Get proven patterns for a specific UI type |\n| `get_business_strategy` | Get business/monetization strategies |\n| `evaluate_design` | Evaluate a design description against principles. Pass base64 PNG screenshots (`before_screenshot`/`after_screenshot`) for a structured before/after pixel diff with `fix_confirmed`, `changed_ratio`, and changed region. Pass `compact: true` to return only scores and violations (drops full principle/pattern bodies) when the full payload is too large. |\n| `search_knowledge` | Search across all principles, patterns, and strategies |\n| `get_checklist` | Get a pre-publish checklist for a UI type |\n| `get_d4d_framework` | Get Design for Delight framework templates |\n| `list_design_systems` | Browse available design systems |\n| `get_design_system` | Get tokens for a specific design system |\n| `compose_system` | Mix tokens from different systems |\n| `get_brand_system` | Get a full system styled like a well-known brand |\n| `audit_page` | Audit HTML/CSS against Raven's quality standards — pass `html` for static audit, or `url` to render headless with optional `scroll_settle` (scroll to bottom + settle reveals) and `viewport` parameters; `containerMaxWidth` makes container checks token-aware. Also flags inline SVG icons that hardcode a color instead of using `currentColor`/a token. Pass `compact: true` to return only scores, violations, and fix_priority (drops embedded base64 screenshots) when the full payload is too large. |\n| `score_page` | Return a per-category (0–10) design score for a page — typography, accessibility, spacing, color, responsive layout, design tokens, structure — derived from the same checks as `audit_page`, plus the overall score/grade, the weakest category, and categories Raven does not mechanically assess (brand, conversion, motion) |\n| `audit_layout` | Evaluate visual rhythm, alignment, and optical balance; detects orphan-stretch (a lonely last-row grid/flex card stretching far wider than siblings) |\n| `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/zero-size) — categorises each as likely-oversight (content vanishing on mobile) vs intentional (decorative) |\n| `audit_contrast` | Compute WCAG contrast ratios for every text element on a rendered page and report AA (4.5:1 / 3:1 large) and AAA pass-fail per element, with delta-to-pass for failures |\n| `suggest_contrast_fix` | Given failing WCAG color pairs, return the minimal fg/bg change that clears the AA/AAA target — concrete passing values to fix `audit_contrast` failures |\n| `audit_url` | Render a live URL at each viewport×theme, scroll-settle, fire interactions, capture real pixels + DOM, then run the page/contrast/responsive/blank-media checks **plus** sliced-image edge-symmetry and hover-state white-wash detection over the captures — every finding tagged confirmed/likely-artifact/inconclusive, ranked by severity. Pass `compact: true` to return only findings and summary (drops per-capture base64 screenshots) when the full payload is too large. |\n| `audit_content` | Per-item content verdicts (pass/warn/fail) for headings, prose, CTAs, labels, captions, metrics & outcomes against UX-writing principles + deterministic heuristics (metric needs number+unit; CTA action-led ≤4 words; prose flags passive/jargon/hedging; caption-vs-heading duplication) — with a before→after rewrite suggestion per item. Pure offline |\n| `audit_typography` | Typographic-**scale** report over rendered DOM text nodes (or a supplied snapshot) — detects the dominant modular-scale ratio and flags off-scale sizes, checks line-height consistency vs the body rhythm, and flags weight ladders >4 weights or non-standard values. Goes beyond `audit_page`'s pass/fail typography checks |\n| `audit_tap_targets` | WCAG 2.5.5 / Apple 44pt **web** tap-target audit — enumerates every interactive element (rendered URL or snapshot) and emits a per-element fix table: selector, role, text, measured w/h, per-axis pixel deficit, and a concrete CSS fix, sorted worst-first |\n| `audit_device_frame` | Flag cropped content in device-mockup frames — `frames` (container box + intrinsic media + object-fit, or a DevTools snippet) detects object-fit:cover crop loss when frame AR ≠ media AR; `clips` (first/last frame PNGs) detects baked-in pan/zoom (Ken Burns); `edge_frames` (PNGs) flags content truncated at a frame edge |\n| `audit_video_playback` | Render a page and observe whether each `