MCP Research

🚀 Research Package for MCP Server for Cursor AI - README

This research package contains comprehensive information about implementing a Model Context Protocol (MCP) server for Cursor AI. The research focuses on how to create an MCP server that can be integrated with Cursor AI to enhance its functionality through custom tools and services.

🚀 Quick Start

To quickly get an overview, start with the comprehensive_report.md file, which contains a comprehensive document of all research results. For specific topics, refer to the individual files mentioned above.

To implement your own MCP server for Cursor AI, follow these steps:

1. Read the implementation_steps.md file for a step-by-step guide.
2. Review the example code in the code examples.
3. Set up the development environment according to the guide.
4. Implement custom tools based on the examples.
5. Configure Cursor AI to use your MCP server.

✨ Features

This research package provides in - depth knowledge and practical examples for implementing an MCP server for Cursor AI, enabling developers to enhance Cursor AI's functionality through custom tools.

📦 Installation

To run the code examples, you need:

• Node.js 14.x or higher
• npm or Yarn package manager
• TypeScript (for TypeScript examples)
• Cursor AI with MCP support

💻 Usage Examples

Basic Usage

The code examples demonstrate different aspects of MCP server implementation:

1. Basic MCP Server (JavaScript): A simple server with text manipulation and calculation tools.

// Code in basic_mcp_server.js
// This is a simple JavaScript MCP server with text tools
// The actual code content will be here in the real basic_mcp_server.js

Advanced Usage

2. Advanced MCP Server (TypeScript): A more complex server with file system operations and security boundaries.

// Code in advanced_mcp_server.ts
// This is an advanced TypeScript MCP server with file system operations
// The actual code content will be here in the real advanced_mcp_server.ts

3. Weather API Integration (TypeScript): An example of integrating an external API (OpenWeatherMap).

// Code in weather_api_integration.ts
// This is an example of integrating OpenWeatherMap API
// The actual code content will be here in the real weather_api_integration.ts

These examples can serve as a starting point for your own MCP server implementation.

📚 Documentation

Directory Structure

• mcp_basics.md: Core concepts of the MCP protocol.
• claude_mcp_implementation.md: Detailed information on Claude's MCP implementation.
• cursor_ai_specifics.md: Specific requirements and integration points for Cursor AI.
• mcp_server_requirements.md: Technical requirements for the MCP server.
• implementation_steps.md: A step - by - step guide to implementing the MCP server.
• comprehensive_report.md: A comprehensive document of the complete research results.
• code_examples/: A directory containing example MCP server implementation code.
  • basic_mcp_server.js: A simple JavaScript MCP server with text tools.
  • advanced_mcp_server.ts: An advanced TypeScript MCP server with file system operations.
  • weather_api_integration.ts: An example of integrating an external API (OpenWeatherMap).

Additional Resources

• Anthropic MCP Documentation
• Cursor Directory
• Smithery.ai - A registry for MCP servers.

📄 Conclusion

This research package provides a comprehensive guide for implementing an MCP server for Cursor AI. By following the guide and examples, developers can create custom tools that enhance Cursor AI's functionality according to specific use cases.