Legal Contract Review Agent
An AI-powered MCP server for analyzing Japanese legal contracts and identifying risks through a RAG-enhanced workflow. It enables clients to search legal knowledge, analyze clause risks, and generate automated contract review reports.
README
Legal Contract Review Agent
AI-powered Japanese legal contract review agent system built with LangGraph, RAG, MCP, and Tool Calling.
Demo

Architecture
┌─────────────┐ ┌──────────────────────────────────────────┐
│ React UI │───▶│ FastAPI Backend │
└─────────────┘ │ │
│ LangGraph Agent Workflow: │
┌─────────────┐ │ parse_contract → retrieve_knowledge │
│ Claude │ │ → analyze_risks → generate_report │
│ Desktop │───▶│ │
│ (MCP Client)│ │ Tools: search_legal_knowledge │
└─────────────┘ │ analyze_clause_risk │
│ generate_suggestion │
│ │
│ RAG: ChromaDB + OpenAI Embeddings │
└──────────────────────────────────────────┘
Tech Stack
- LLM: OpenAI GPT-4o
- Agent Framework: LangGraph (StateGraph)
- RAG: ChromaDB + text-embedding-3-small
- MCP: FastMCP (Python)
- Backend: FastAPI
- Frontend: React + Vite + TypeScript
- Deployment: Docker Compose
Quick Start
Prerequisites
- Docker & Docker Compose
- OpenAI API Key
Setup & Run
cd legal-contract-agent
# Create .env from template and add your OpenAI API Key
cp .env.example .env
# Edit .env: OPENAI_API_KEY=sk-your-key-here
# Build and start all services
docker compose up --build
Open http://localhost:5173 — paste a Japanese contract and click "契約書を審査する".
To stop:
docker compose down # Stop containers
docker compose down -v # Stop and remove data volumes
Run Without Docker (Alternative)
# Install Python dependencies
pip install .
# Install frontend dependencies
cd frontend && npm install && cd ..
# Terminal 1: Start backend
uvicorn backend.main:app --reload
# Terminal 2: Start frontend
cd frontend && npm run dev
MCP Server (for Claude Desktop)
python -m backend.mcp.server
Add to Claude Desktop config:
{
"mcpServers": {
"legal-review": {
"command": "python",
"args": ["-m", "backend.mcp.server"],
"cwd": "/path/to/legal-contract-agent"
}
}
}
Project Structure
backend/
├── main.py # FastAPI entry point
├── Dockerfile # Backend container image
├── agent/
│ ├── graph.py # LangGraph workflow
│ ├── nodes.py # Agent node functions
│ ├── state.py # Agent state definition
│ └── tools.py # LangChain tools
├── rag/
│ ├── store.py # ChromaDB vector store
│ └── loader.py # Knowledge loader
├── mcp/
│ └── server.py # MCP server
└── data/
└── legal_knowledge.json # Legal knowledge (20 entries)
frontend/
├── Dockerfile # Frontend container image
└── src/
├── App.tsx # Main UI
└── App.css # Styles
docker-compose.yml # Container orchestration
Key Design Decisions
- LangGraph over simple chain: Supports conditional branching, state management, and is extensible for multi-agent collaboration
- RAG: Grounds agent responses in reliable legal knowledge rather than relying solely on LLM memory
- MCP: Standardized AI tool protocol enabling any client (Claude Desktop, etc.) to invoke contract review capabilities
- Tool Calling: Agent autonomously decides when to invoke which tool, demonstrating autonomous decision-making
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