MCP Server Template For Better Ai Coding

🚀 MCP Server Template for More Efficient AI Coding

This template offers a streamlined basic implementation for building a Model Context Protocol (MCP) server in Python. It aims to make the development of AI-assisted MCP tools more efficient and intuitive.

🚀 Quick Start

Prerequisites

• Python 3.12+
• Dependencies:
  • mcp>=1.4.1
  • httpx>=0.28.1
  • starlette>=0.46.1
  • uvicorn>=0.15.0

Installation

Install Dependencies

Use the following command to install the required Python packages:

pip install mcp httpx starlette uvicorn

Clone the Repository

Clone this template to your local machine:

git clone https://github.com/yourusername/mcp-server-template.git
cd mcp-server-template

Usage

Start the Server

Run the following command in the terminal to start the MCP server:

uvicorn main:app --reload

This will start a development server on the default port 8000 with auto-reloading enabled.

Call the API

Use the following curl command to test the basic API functionality:

curl http://localhost:8000/api/hello

✨ Features

• Ready-to-use MCP server implementation
• Configurable transport modes (standard input/output, SSE)
• Example weather service integration (NWS API)
• Clear and well-documented code structure
• Minimized dependencies
• Embedded MCP specifications and documentation to enhance the understanding ability of AI tools

📚 Documentation

Cursor Rules Integration

This project uses Cursor Rules to improve the quality of AI coding assistance, incorporating patterns from Awesome Cursor Rules.

• Code Cleanliness Guidelines: Built-in clean code rules help maintain consistency and quality.
• Enhanced AI Understanding: The rules provide context for the AI assistant, enabling it to generate higher-quality code.
• Standardized Patterns: Follow the best practices for MCP server implementation.

Cursor Rules assist both AI coding assistants and human developers in maintaining high standards of code quality and adhering to established best practices.

Integrated MCP Documentation

This template includes comprehensive MCP documentation directly embedded in the project:

• Complete MCP Specification (protocals/mcp.md): Details the protocol for how AI models interact with external tools and resources. This allows AI tools to understand MCP concepts without external references.
• Python SDK Usage Guide (protocals/sdk.md): Detailed documentation on the MCP Python SDK, making it easier for AI tools to provide accurate code suggestions and gain a comprehensive understanding of the library's functionality.
• Example Implementation (protocals/example_weather.py): A practical weather service implementation demonstrating real-world MCP server patterns and best practices.

Embedding these resources in the project enables AI coding assistants to better understand MCP concepts and provide more accurate, context-aware suggestions during development.

Project Structure

The typical directory structure of the project is as follows:

mcp-server-template/
├── main.py           # Main application entry point
├── config.py         # Configuration management
├── routes/           # Route definitions
│   └── api.py        # API routes
├── middleware/       # Middleware
│   └── auth.py       # Authentication middleware
└── templates/        # Template files
    └── index.html     # Default template

Learning Resources

• MCP Official Documentation
• Protocol Documentation
• SDK Usage Guide

🤝 Contribution

Contributions are welcome! Please feel free to submit a Pull Request.

📄 License

This project is licensed under the MIT License. Please refer to the LICENSE file for details.