How to Create a Model Context Protocol (MCP) Server

This repository serves as a comprehensive guide for creating Model Context Protocol (MCP) servers. MCP is a protocol designed to enable AI models to interact with external tools and services in a standardized way.

Table of Contents

1. Introduction to MCP
2. Getting Started
3. Core Concepts
4. Implementation Guide
5. Best Practices
6. Examples

Introduction to MCP

Model Context Protocol (MCP) is a standardized way for AI models to interact with external tools and services. It defines how:
- Tools are described and presented to models
- Models can request tool execution
- Results are returned to models

Getting Started

To create an MCP server, you'll need:
- Node.js environment
- Basic understanding of REST APIs
- Familiarity with async/await patterns
- Understanding of JSON schemas

Core Concepts

1. Tool Definitions
- Function schemas
- Parameter validation
- Return types

2. Request/Response Flow
- Tool invocation
- Result handling
- Error management

3. Authentication & Security
- API keys
- Rate limiting
- Access control

Implementation Guide

Detailed implementation steps will be added in separate markdown files covering:
1. Basic server setup
2. Tool definition implementation
3. Request handling
4. Response formatting
5. Error handling
6. Testing and validation

Best Practices

- Keep tool descriptions clear and concise
- Implement proper error handling
- Use TypeScript for better type safety
- Follow security best practices
- Implement proper logging
- Add comprehensive documentation

Examples

Example implementations will be provided for:
- Basic tool server
- File operation tools
- API integration tools
- Database operation tools

Contributing

Contributions are welcome! Please feel free to submit pull requests or create issues for any improvements or suggestions.

License

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