LangChain Agent MCP Server

A production-ready MCP server exposing LangChain agent capabilities through the Model Context Protocol, deployed on Google Cloud Run.

🚀 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:

   git clone https://github.com/mcpmessenger/LangchainMCP.git
   cd LangchainMCP

2. Install dependencies:

   # Windows
   py -m pip install -r requirements.txt
   
   # Linux/Mac
   pip install -r requirements.txt

3. Set up environment variables: Create a .env file:

   OPENAI_API_KEY=your-openai-api-key-here
   OPENAI_MODEL=gpt-4o-mini
   PORT=8000

4. Run the server:

   # 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 - Windows deployment guide
• DEPLOY_CLOUD_RUN.md - General deployment guide
• QUICK_DEPLOY.md - Quick reference

Quick Deploy

# 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

GET /mcp/manifest

Returns the MCP manifest declaring available tools.

Response:

{
  "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

POST /mcp/invoke
Content-Type: application/json

{
  "tool": "agent_executor",
  "arguments": {
    "query": "What is the capital of France?"
  }
}

Response:

{
  "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 - Complete documentation with examples (GitHub Pages)

Quick Links:

• Getting Started - Set up and run locally
• Examples - Code examples including "Build a RAG agent in 10 lines"
• Deployment Guide - Deploy to Google Cloud Run
• API Reference - Complete API documentation
• Troubleshooting - Common issues and solutions

Build Docs Locally:

# Windows
.\build-docs.ps1 serve

# Linux/Mac
./build-docs.sh serve

Additional Guides:

• README_BACKEND.md - Complete technical documentation
• DEPLOY_CLOUD_RUN_WINDOWS.md - Windows deployment guide
• INSTALL_PREREQUISITES.md - Prerequisites installation
• SLASHMCP_INTEGRATION.md - SlashMCP integration guide

🧪 Testing

# 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 for detailed instructions.

Docker (Local/Other Platforms)

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
• Deployed on Google Cloud Run
• Uses FastAPI for the web framework

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Status: ✅ Production-ready and deployed on Google Cloud Run