README.md•9.17 kB
# LangChain Agent MCP Server
> **A production-ready MCP server exposing LangChain agent capabilities through the Model Context Protocol, deployed on Google Cloud Run.**
[](https://github.com/mcpmessenger/LangchainMCP)
[](https://github.com/mcpmessenger/LangchainMCP)
[](https://github.com/mcpmessenger/LangchainMCP/blob/main/LICENSE)
## 🚀 Overview
This is a **standalone backend service** that wraps a LangChain agent as a single, high-level MCP Tool. The server is built with **FastAPI** and deployed on **Google Cloud Run**, providing a scalable, production-ready solution for exposing AI agent capabilities to any MCP-compliant client.
**Live Service:** https://langchain-agent-mcp-server-554655392699.us-central1.run.app
## ✨ Features
- ✅ **MCP Compliance** - Full Model Context Protocol support
- ✅ **LangChain Agent** - Multi-step reasoning with ReAct pattern
- ✅ **Google Cloud Run** - Scalable, serverless deployment
- ✅ **Tool Support** - Extensible framework for custom tools
- ✅ **Production Ready** - Error handling, logging, and monitoring
- ✅ **Docker Support** - Containerized for easy deployment
## 🏗️ Architecture
| Component | Technology | Purpose |
| :--- | :--- | :--- |
| **Backend Framework** | FastAPI | High-performance, asynchronous web server |
| **Agent Framework** | LangChain | Multi-step reasoning and tool execution |
| **Deployment** | Google Cloud Run | Serverless, auto-scaling hosting |
| **Containerization** | Docker | Consistent deployment environment |
| **Protocol** | Model Context Protocol (MCP) | Standardized tool and context sharing |
## 🛠️ Quick Start
### Prerequisites
- Python 3.11+
- OpenAI API key
- Google Cloud account (for Cloud Run deployment)
- Docker (optional, for local testing)
### Local Development
1. **Clone the repository:**
```bash
git clone https://github.com/mcpmessenger/LangchainMCP.git
cd LangchainMCP
```
2. **Install dependencies:**
```powershell
# Windows
py -m pip install -r requirements.txt
# Linux/Mac
pip install -r requirements.txt
```
3. **Set up environment variables:**
Create a `.env` file:
```env
OPENAI_API_KEY=your-openai-api-key-here
OPENAI_MODEL=gpt-4o-mini
PORT=8000
```
4. **Run the server:**
```powershell
# Windows
py run_server.py
# Linux/Mac
python run_server.py
```
5. **Test the endpoints:**
- Health: http://localhost:8000/health
- Manifest: http://localhost:8000/mcp/manifest
- API Docs: http://localhost:8000/docs
## ☁️ Google Cloud Run Deployment
The server is designed for deployment on **Google Cloud Run**. See our comprehensive deployment guides:
- **[DEPLOY_CLOUD_RUN_WINDOWS.md](DEPLOY_CLOUD_RUN_WINDOWS.md)** - Windows deployment guide
- **[DEPLOY_CLOUD_RUN.md](DEPLOY_CLOUD_RUN.md)** - General deployment guide
- **[QUICK_DEPLOY.md](QUICK_DEPLOY.md)** - Quick reference
### Quick Deploy
```powershell
# Windows PowerShell
.\deploy-cloud-run.ps1 -ProjectId "your-project-id" -Region "us-central1"
# Linux/Mac
./deploy-cloud-run.sh your-project-id us-central1
```
### Current Deployment
- **Service URL:** https://langchain-agent-mcp-server-554655392699.us-central1.run.app
- **Project:** slashmcp
- **Region:** us-central1
- **Status:** ✅ Live and operational
## 📡 API Endpoints
### MCP Endpoints
#### Get Manifest
```http
GET /mcp/manifest
```
Returns the MCP manifest declaring available tools.
**Response:**
```json
{
"name": "langchain-agent-mcp-server",
"version": "1.0.0",
"tools": [
{
"name": "agent_executor",
"description": "Execute a complex, multi-step reasoning task...",
"inputSchema": {
"type": "object",
"properties": {
"query": {
"type": "string",
"description": "The user's query or task"
}
},
"required": ["query"]
}
}
]
}
```
#### Invoke Tool
```http
POST /mcp/invoke
Content-Type: application/json
{
"tool": "agent_executor",
"arguments": {
"query": "What is the capital of France?"
}
}
```
**Response:**
```json
{
"content": [
{
"type": "text",
"text": "The capital of France is Paris."
}
],
"isError": false
}
```
### Other Endpoints
- `GET /` - Server information
- `GET /health` - Health check
- `GET /docs` - Interactive API documentation (Swagger UI)
## 🔧 Configuration
### Environment Variables
| Variable | Description | Default | Required |
|----------|-------------|---------|----------|
| `OPENAI_API_KEY` | OpenAI API key | - | ✅ Yes |
| `OPENAI_MODEL` | OpenAI model to use | `gpt-4o-mini` | No |
| `PORT` | Server port | `8000` | No |
| `API_KEY` | Optional API key for authentication | - | No |
| `MAX_ITERATIONS` | Maximum agent iterations | `10` | No |
| `VERBOSE` | Enable verbose logging | `false` | No |
## 📚 Documentation
📖 **[Full Documentation Site](https://mcpmessenger.github.io/LangchainMCP/)** - Complete documentation with examples (GitHub Pages)
**Quick Links:**
- **[Getting Started](docs/getting-started.md)** - Set up and run locally
- **[Examples](docs/examples.md)** - Code examples including **"Build a RAG agent in 10 lines"**
- **[Deployment Guide](docs/deployment.md)** - Deploy to Google Cloud Run
- **[API Reference](docs/api-reference.md)** - Complete API documentation
- **[Troubleshooting](docs/troubleshooting.md)** - Common issues and solutions
**Build Docs Locally:**
```powershell
# Windows
.\build-docs.ps1 serve
# Linux/Mac
./build-docs.sh serve
```
**Additional Guides:**
- **[README_BACKEND.md](README_BACKEND.md)** - Complete technical documentation
- **[DEPLOY_CLOUD_RUN_WINDOWS.md](DEPLOY_CLOUD_RUN_WINDOWS.md)** - Windows deployment guide
- **[INSTALL_PREREQUISITES.md](INSTALL_PREREQUISITES.md)** - Prerequisites installation
- **[SLASHMCP_INTEGRATION.md](SLASHMCP_INTEGRATION.md)** - SlashMCP integration guide
## 🧪 Testing
```powershell
# Test health endpoint
Invoke-WebRequest -Uri "https://langchain-agent-mcp-server-554655392699.us-central1.run.app/health"
# Test agent invocation
$body = @{
tool = "agent_executor"
arguments = @{
query = "What is 2+2?"
}
} | ConvertTo-Json
Invoke-WebRequest -Uri "https://langchain-agent-mcp-server-554655392699.us-central1.run.app/mcp/invoke" `
-Method POST `
-ContentType "application/json" `
-Body $body
```
## 🏗️ Project Structure
```
.
├── src/
│ ├── main.py # FastAPI application with MCP endpoints
│ ├── agent.py # LangChain agent definition and tools
│ ├── mcp_manifest.json # MCP manifest configuration
│ └── start.sh # Cloud Run startup script
├── tests/
│ └── test_mcp_endpoints.py # Test suite
├── Dockerfile # Container configuration
├── requirements.txt # Python dependencies
├── deploy-cloud-run.ps1 # Windows deployment script
├── deploy-cloud-run.sh # Linux/Mac deployment script
└── cloudbuild.yaml # Cloud Build configuration
```
## 🚀 Deployment Options
### Google Cloud Run (Recommended)
- **Scalable** - Auto-scales based on traffic
- **Serverless** - Pay only for what you use
- **Managed** - No infrastructure to manage
- **Fast** - Low latency with global CDN
See [DEPLOY_CLOUD_RUN_WINDOWS.md](DEPLOY_CLOUD_RUN_WINDOWS.md) for detailed instructions.
### Docker (Local/Other Platforms)
```bash
docker build -t langchain-agent-mcp-server .
docker run -p 8000:8000 -e OPENAI_API_KEY=your-key langchain-agent-mcp-server
```
## 📊 Performance
- **P95 Latency:** < 5 seconds for standard 3-step ReAct chains
- **Scalability:** Horizontal scaling on Cloud Run
- **Uptime:** 99.9% target (Cloud Run SLA)
- **Throughput:** Handles concurrent requests efficiently
## 🔒 Security
- API key authentication (optional)
- Environment variable management
- Secret Manager integration (Cloud Run)
- HTTPS by default (Cloud Run)
- CORS configuration
## 🤝 Contributing
We welcome contributions! Please see our contributing guidelines.
1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Submit a pull request
## 📜 License
This project is licensed under the MIT License.
## 🔗 Links
- **GitHub Repository:** https://github.com/mcpmessenger/LangchainMCP
- **Live Service:** https://langchain-agent-mcp-server-554655392699.us-central1.run.app
- **API Documentation:** https://langchain-agent-mcp-server-554655392699.us-central1.run.app/docs
- **Model Context Protocol:** https://modelcontextprotocol.io/
## 🙏 Acknowledgments
- Built with [LangChain](https://www.langchain.com/)
- Deployed on [Google Cloud Run](https://cloud.google.com/run)
- Uses [FastAPI](https://fastapi.tiangolo.com/) for the web framework
---
**Status:** ✅ Production-ready and deployed on Google Cloud Run
