mcp-modelservice-sdk 0.2.6

A CLI for the MCP Modelservice Example

mcp-modelservice-sdk

🚀 Easily build and deploy MCP (Model Context Protocol) services from your Python functions

mcp-modelservice-sdk is a powerful toolkit that transforms your Python functions into fully-featured MCP services with minimal configuration. Perfect for developers who want to quickly expose their Python code as MCP tools without the complexity of manual service setup.

✨ Key Features

• 📦 Zero-Config Packaging: Convert Python functions to MCP services instantly
• 🚀 One-Command Deployment: Start services with a single command
• 🔄 Smart Auto-Routing: Automatic endpoint generation based on your code structure
• 🌐 Production Ready: Built-in support for Docker, cloud platforms, and scaling
• 🛠️ Developer Friendly: Interactive testing interface and comprehensive documentation
• 🎯 Type Safe: Full support for Python type hints and automatic validation

🚀 Quick Start

Installation

# Using pip
pip install mcp-modelservice-sdk

# Using uv (recommended)
pip install uv
uv pip install mcp-modelservice-sdk

Basic Usage

1. Create your Python functions:

# my_tools.py
def add_numbers(a: float, b: float) -> float:
    """Add two numbers together"""
    return a + b

def get_weather(city: str) -> str:
    """Get weather information for a city"""
    return f"Weather in {city}: Sunny, 25°C"

2. Run as MCP service:

# Start local development server
mcp-modelservice run --source-path my_tools.py --port 8080

# Or with uv
uvx mcp-modelservice-sdk run --source-path my_tools.py --port 8080

3. Test your service:
   • Visit http://localhost:8080/mcp for interactive testing
   • Use any MCP client to connect and call your functions

Production Packaging

# Package for deployment
mcp-modelservice package --source-path ./my_code --output my-service.zip

# Extract and deploy
unzip my-service.zip
cd my-service/project
python main.py

🏗️ How It Works

The SDK automatically:

• Discovers all functions in your Python files
• Converts them to MCP-compatible tools with proper schemas
• Generates REST endpoints and documentation
• Packages everything into deployable services
• Provides interactive testing interfaces

Architecture Modes

• Composed Mode: All tools accessible from a single endpoint
• Routed Mode: Directory-based routing with separate endpoints per module

🌐 Deployment Options

Deploy anywhere Python runs:

• Local Development: Direct execution with python main.py
• Docker: Pre-configured Dockerfile included
• Cloud Platforms: Compatible with Heroku, AWS Lambda, Google Cloud Run, Azure
• Traditional Servers: Standard WSGI/ASGI deployment

📚 Client Integration

Python Client Example

import requests

def call_tool(tool_name, params):
    response = requests.post(
        "http://localhost:8080/mcp",
        json={
            "jsonrpc": "2.0",
            "method": tool_name,
            "params": params,
            "id": 1
        }
    )
    return response.json()

# Use your functions
result = call_tool("add_numbers", {"a": 5, "b": 3})
print(result)  # {"jsonrpc": "2.0", "result": 8, "id": 1}

FastMCP Client Example

from fastmcp import FastMCP

client = FastMCP("http://localhost:8080")
result = await client.call_tool("add_numbers", {"a": 5, "b": 3})

⚙️ Configuration

Command Line Options

Option	Description	Default
--source-path	Path to Python files/directory	Current directory
--port	Service port	8080
--host	Service host	127.0.0.1
--mcp-name	Service name	Auto-generated

Environment Variables

# .env file
HOST=0.0.0.0
PORT=8080
MCP_SERVER_NAME=my-service
LOG_LEVEL=INFO

🤝 Use Cases

Perfect for:

• Rapid Prototyping: Quickly expose Python functions as web services
• Microservices: Convert existing Python modules to independent services
• API Generation: Auto-generate REST APIs from Python functions
• Tool Integration: Make Python tools accessible to MCP clients
• Development Testing: Interactive testing of Python functions

🛠️ Requirements

• Python: 3.10 or higher
• Dependencies: FastAPI, FastMCP, Pydantic, Uvicorn (auto-installed)

📖 Documentation & Support

• GitHub Repository: https://github.com/modelcontextprotocol/mcp-modelservice-sdk
• Full Documentation: Available in the GitHub repository
• Issue Tracking: Report bugs and request features on GitHub
• Community: Join discussions and get help

🤝 Contributing

We welcome contributions! Please see our Contributing Guide for details.

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

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Made with ❤️ for the Python and MCP communities

Ready to transform your Python functions into powerful MCP services? Install mcp-modelservice-sdk today!