ReftrixMCP

Web design knowledge base platform -- layout analysis, motion detection, and quality evaluation via MCP tools.

For frontend engineers, designers, and AI-agent builders who want to analyze real websites and retrieve reusable UI patterns via Claude or any MCP client.

ReftrixMCPは、Webデザインパターンをベクトル検索(pgvector HNSW)と RAGで検索可能なナレッジベースに集約し、MCPツール経由でClaude等の AIエージェントと統合するプラットフォームです。

主要機能: レイアウト分析 / モーション検出 / 品質評価 / セマンティック検索 / レスポンシブ解析

20のMCPツールを提供: Layout(5) / Motion(2) / Quality(3) / Page(2) / Narrative(1) / Background(1) / Responsive(1) / Style(1) / Brief(1) / Project(2) / System(1)

詳細な日本語ドキュメント: docs/README.ja.md

What it does

• Layout analysis -- auto-detect sections (hero, feature, CTA, etc.), extract grid/typography, and generate React/Vue/HTML code

• Motion detection -- discover CSS/JS animations with frame capture (15 px/frame video mode), CLS detection via Pixelmatch

• Quality evaluation -- score designs on three axes (originality, craftsmanship, contextuality) with anti-AI-cliche detection

• Semantic search -- find layout, motion, narrative, background, and responsive patterns via pgvector HNSW hybrid search

• Vision integration -- Ollama llama3.2-vision for richer layout, motion, and narrative understanding

• Code generation -- convert analyzed sections to React, Vue, or plain HTML with matched motion patterns

Why ReftrixMCP

Quickstart

Run page.analyze on any URL in under 5 minutes.

Prerequisites

Node.js 20+, pnpm 10+, Docker & Docker Compose, Ollama

Setup

git clone https://github.com/TKMD/ReftrixMCP.git && cd ReftrixMCP
pnpm install
cp .env.example .env.local                       # edit DATABASE_URL / REDIS_URL as needed
cp .env.local packages/database/.env             # Prisma CLI requires this copy
pnpm docker:up                                   # PostgreSQL 18 + pgvector + Redis
pnpm db:migrate && pnpm db:seed
pnpm build
pnpm exec playwright install chromium            # browser for page crawling
curl -fsSL https://ollama.com/install.sh | sh    # install Ollama
ollama pull llama3.2-vision                      # vision model (~2 GB)
ollama serve                                     # keep running in a separate terminal

Note: If you change .env.local, also update packages/database/.env. page.analyze workers start automatically -- no manual worker launch needed. See Getting Started for GPU configuration and details.

Connect to Claude

Add to your MCP config:

• Claude Desktop: ~/Library/Application Support/Claude/claude_desktop_config.json (macOS)

• MCP Client CLI: .mcp.json in the project root or ~/.claude/.mcp.json

{
  "mcpServers": {
    "reftrix": {
      "command": "node",
      "args": ["/absolute/path/to/ReftrixMCP/apps/mcp-server/dist/index.js"],
      "env": {
        "NODE_ENV": "development",
        "DATABASE_URL": "postgresql://reftrix:change_me@localhost:26432/reftrix?schema=public",
        "REDIS_URL": "redis://localhost:27379",
        "OLLAMA_BASE_URL": "http://localhost:11434"
      }
    }
  }
}

Replace change_me with a secure password. Port 26432 = standard 5432 + 21000 offset.

Example tools

ReftrixMCP provides 20 MCP tools. Key examples:

• layout.ingest -- fetch a web page, take a screenshot, and extract section patterns

• layout.search -- semantic search over layout sections by natural-language query

• motion.detect -- detect CSS/JS animations with video-mode frame capture

• quality.evaluate -- score design quality on originality, craftsmanship, and contextuality

• page.analyze -- unified analysis: layout + motion + quality in one call (async via BullMQ)

• responsive.search -- search responsive analysis results by viewport and breakpoint

Full tool reference: MCP Tools Guide

Architecture

MCP Client (Claude Desktop / Code)  --stdio-->  MCP Server (20 tools, Zod)
  +-- Service Layer: Playwright, Sharp+Pixelmatch, DOMPurify
  +-- ML Layer: ONNX Runtime (multilingual-e5-base, 768-dim)
  +-- BullMQ Workers: page.analyze, quality.evaluate
  +-- PostgreSQL 18 + pgvector 0.8 (HNSW, tsvector)  +  Redis 7

Documentation

Known limitations

• CPU-mode embedding takes ~2-5 s per text; GPU recommended for batch workloads

• Minimum 8 GB RAM; 16 GB recommended for concurrent analysis

• First embedding call downloads ~400 MB model (multilingual-e5-base)

• page.analyze workers auto-start via WorkerSupervisor; manual launch is not required

• Vision analysis (layout, motion, narrative) requires Ollama + llama3.2-vision running locally

License

AGPL-3.0-only -- see LICENSE.

Network use requires source disclosure per Section 13. Source: github.com/TKMD/ReftrixMCP Commercial license: licence@reftrix.io

Contributing

See CONTRIBUTING.md.

Security

Report vulnerabilities per SECURITY.md. Privacy: docs/legal/PRIVACY_POLICY.md | Third-party licenses: THIRDPARTY_LICENSES.md