MCP Servers for Cursor AI - README

# MCP Servers for Cursor AI - README This research package contains comprehensive information on implementing Model Context Protocol (MCP) servers specifically for Cursor AI integration. The research focuses on how to create MCP servers that can be integrated with Cursor AI to enhance its capabilities through custom tools and services. ## Directory Structure - **mcp_basics.md**: Core concepts of the Model Context Protocol - **claude_mcp_implementation.md**: Details on Claude's MCP implementation - **cursor_ai_specifics.md**: Cursor AI's specific requirements and integration points - **mcp_server_requirements.md**: Technical requirements for MCP servers - **implementation_steps.md**: Step-by-step guide for implementing MCP servers - **comprehensive_report.md**: Complete research findings in a single document - **code_examples/**: Directory containing sample MCP server implementations - **basic_mcp_server.js**: Simple JavaScript MCP server with text tools - **advanced_mcp_server.ts**: Advanced TypeScript MCP server with file system operations - **weather_api_integration.ts**: Example of integrating with external APIs ## Getting Started For a quick overview, start with the comprehensive_report.md file, which contains all the research findings in a single document. For specific topics, refer to the individual files listed 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 code examples in the code_examples/ directory 3. Set up your development environment as described in the guide 4. Implement your custom tools based on the examples 5. Configure Cursor AI to use your MCP server ## Code Examples The code examples demonstrate different aspects of MCP server implementation: 1. **Basic MCP Server (JavaScript)**: A simple server with text manipulation and calculation tools 2. **Advanced MCP Server (TypeScript)**: A more sophisticated server with file system operations and security boundaries 3. **Weather API Integration (TypeScript)**: An example of integrating with external APIs (OpenWeatherMap) These examples can be used as starting points for your own MCP server implementations. ## Requirements To run the code examples, you'll need: - Node.js 14.x or higher - npm or yarn package manager - TypeScript (for TypeScript examples) - Cursor AI with MCP support ## Additional Resources - [Anthropic MCP Documentation](https://docs.anthropic.com/en/docs/build-with-claude/mcp) - [Cursor Directory](https://cursor.directory/mcp) - [Smithery.ai](https://smithery.ai) - Registry of MCP servers ## Conclusion This research package provides a comprehensive guide to implementing MCP servers for Cursor AI. By following the guidelines and examples, developers can create custom tools that enhance Cursor AI's capabilities for specific use cases.