Langchain Mcp — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited Langchain Mcp (Agent Skill) and scored it 100/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
Findings & checks · 0 flagged
Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
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Website • Installation • Features • Documentation
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LangChain MCP is a Model Context Protocol (MCP) server that provides semantic search across the entire LangChain ecosystem. Build AI applications faster with instant access to documentation and source code for LangChain, LangGraph, LangSmith, and DeepAgents.
<img src="img/homepage.png" alt="LangChain MCP Homepage" width="800">
# Install globally
npm install -g langchain-mcp
# Login with Google
langchain-mcp login
# Add to Claude Code
claude mcp add langchain-mcp -- npx langchain-mcpAdd the following configuration to your client's config file:
Claude Desktop
~/Library/Application Support/Claude/claude_desktop_config.json%APPDATA%\Claude\claude_desktop_config.jsonCursor
~/.cursor/mcp.json%USERPROFILE%\.cursor\mcp.json{
"mcpServers": {
"langchain-mcp": {
"command": "npx",
"args": ["langchain-mcp"]
}
}
}langchain-mcp login # Login via Google OAuth
langchain-mcp status # Check usage and remaining credits
langchain-mcp logout # Logout and clear credentials| Tool | Description | Parameters |
|---|---|---|
search_docs | Search documentation, references, and tutorials | query, limit (default: 5) |
search_langchain_code | Search LangChain source code | query, language (py/js), limit |
search_langgraph_code | Search LangGraph source code | query, language (py/js), limit |
search_deepagents_code | Search DeepAgents source code | query, language (py/js), limit |
#### Project Structure
langchain-MCP/
├── packages/
│ ├── ingest/ # Python - Data ingestion (uv)
│ ├── api/ # TypeScript - API server (Express)
│ ├── mcp-server/ # TypeScript - MCP client (npm package)
│ └── mcp-server-local/ # TypeScript - Local MCP server (dev)
├── config/
│ └── settings.json # Shared configuration
└── deploy.sh # Deployment script#### Architecture
<img src="img/Architecture.png" alt="Architecture" width="600">
#### Setup Development Environment
1. Ingest Documentation & Source Code
cd packages/ingest
uv sync
uv run ingest --list # List available repositories
uv run ingest docs # Ingest documentation only
uv run ingest # Ingest all (docs + code)2. Run API Server
cd packages/api
npm install
npm run dev # Development server on port 30003. Test Local MCP Server
cd packages/mcp-server-local
npm install
npm run dev#### Configuration
All settings in config/settings.json:
{
"embedding": {
"provider": "openrouter",
"model": "qwen/qwen3-embedding-8b"
},
"chromadb": {
"path": "./data/chroma"
},
"chunking": {
"docs": { "chunk_size": 2000, "chunk_overlap": 200 },
"code": { "chunk_size": 4000, "chunk_overlap": 200 }
},
"repos": [
{
"name": "langchain",
"url": "https://github.com/langchain-ai/langchain",
"type": "code",
"languages": ["python", "javascript"]
}
]
}#### Supported Embedding Providers
sentence-transformer (local)openaicoheregoogleollamaopenrouter (default)See ChromaDB Integrations for more options.
The project includes automated deployment scripts for VPS hosting:
# Manual deployment
./deploy.sh
# GitHub Actions (production branch)
git push origin main:productionDeployment includes:
Forking and contributions are welcome!
MIT License - see the LICENSE file for details.
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Built with ❤️ by [baixianger](https://github.com/baixianger)
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~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.