Awesome-MCP-Scaffold

# 🎯 Cursor IDE Usage Guide This guide provides a detailed introduction on how to fully utilize the features and configurations of **Awesome MCP Scaffold** in Cursor IDE. ## 🌟 Why Choose Cursor? Cursor is a modern IDE designed specifically for AI-assisted development, perfectly integrated with the MCP protocol: - **Native MCP support**: Direct connection and usage of MCP servers - **Smart code completion**: AI suggestions based on context - **Natural language programming**: Describe requirements in natural language, AI generates code - **Real-time collaboration**: Seamless collaboration with AI assistant ## 📁 Project Configuration ### Cursor Rules Configuration The project includes pre-configured Cursor rule files: ``` .cursor/ ├── rules/ │ ├── mcp-development-guide.mdc # MCP development guide │ ├── mcp-testing-patterns.mdc # Testing patterns guide │ └── streamable-http-production.mdc # Production deployment guide ``` These rules automatically tell Cursor: - MCP best practices - Code structure specifications - Testing strategies - Deployment patterns ### Auto-Applied Rules When you open the project in Cursor, the following rules automatically take effect: 1. **MCP server development standards** 2. **FastMCP framework usage guidance** 3. **Streamable HTTP transport optimization** 4. **Test-driven development patterns** 5. **Production deployment best practices** ## 🔧 Configure MCP Server ### 1. Add MCP Server in Cursor Settings Open Cursor settings (`Cmd/Ctrl + ,`), find the MCP configuration section, and add: ```json { "mcpServers": { "awesome-mcp-scaffold": { "command": "python", "args": ["-m", "server.main"], "cwd": "/path/to/your/Awesome-MCP-Scaffold", "env": { "TRANSPORT": "stdio", "ENVIRONMENT": "development", "DEBUG": "true" } } } } ``` ### 2. Verify Connection In Cursor, press `Cmd/Ctrl + Shift + P`, search for "MCP", you should see: - **MCP: Connect to Server** - **MCP: List Tools** - **MCP: List Resources** ## 🛠️ Using MCP Features ### Calculator Tool In Cursor, you can directly ask AI to perform calculations: ``` User: "Help me calculate BMI, weight 70kg, height 1.75m" AI: Let me calculate BMI for you... [Calls calculate_bmi tool] Result: BMI = 22.86 (Normal weight) ``` ### Text Processing ``` User: "Analyze the statistics of this text: 'Hello World! This is a test.'" AI: Let me analyze text statistics... [Calls text_statistics tool] Result: - Word count: 6 - Character count: 29 - Sentence count: 2 - Average word length: 4.83 ``` ### File Operations ``` User: "Create a JSON file in the workspace directory containing user data" AI: Let me create the JSON file... [Calls write_json_file tool] Result: File created at workspace/users.json ``` ### System Information ``` User: "Show current system memory usage" AI: Let me get system information... [Reads system://memory resource] Result: Memory usage 45%, available memory 8.2GB ``` ## 🎨 Development Workflow ### 1. Create New Tool Using Cursor's natural language programming: ``` User: "Create a new MCP tool for generating random passwords" AI will automatically: 1. Create new file in server/tools/ 2. Implement password generation logic 3. Register tool to main module 4. Add corresponding tests ``` ### 2. Code Review ``` User: "Review the code quality of this function" AI will use the built-in code_review prompt template to provide: - Code quality analysis - Performance optimization suggestions - Security checks - Best practice recommendations ``` ### 3. Test Generation ``` User: "Generate unit tests for this tool" AI will: 1. Analyze tool functionality 2. Generate test cases 3. Include boundary condition tests 4. Add error handling tests ``` ## 🚀 Advanced Features ### Smart Refactoring Cursor can understand MCP architecture and provide intelligent refactoring suggestions: ``` User: "Refactor this tool to better comply with MCP best practices" AI will: - Analyze current code structure - Apply MCP development standards - Optimize error handling - Improve docstrings ``` ### Automated Testing ``` User: "Run all tests and fix failed tests" AI will: 1. Execute make test 2. Analyze test results 3. Automatically fix simple test failures 4. Provide solutions for complex issues ``` ### Deployment Optimization ``` User: "Optimize this MCP server for production deployment" AI will: - Apply production configuration best practices - Optimize performance settings - Add monitoring and logging - Configure security settings ``` ## 🎯 Real-World Use Cases ### Scenario 1: API Integration ``` User: "Integrate OpenWeatherMap API as an MCP tool" AI workflow: 1. Create new tool module 2. Implement API call logic 3. Add error handling and retry 4. Create corresponding tests 5. Update documentation ``` ### Scenario 2: Data Analysis ``` User: "Create a data analysis tool that can process CSV files" AI will: 1. Implement CSV reading tool 2. Add statistical data analysis 3. Create visualization suggestions 4. Integrate into MCP framework ``` ### Scenario 3: Automation Tasks ``` User: "Create a scheduled task tool that can periodically clean temporary files" AI will: 1. Design task scheduling system 2. Implement file cleanup logic 3. Add configuration management 4. Create monitoring functionality ``` ## 🔍 Debugging Tips ### 1. MCP Connection Debugging If there are MCP connection issues: ``` User: "MCP server connection failed, help me debug" AI will check: - Server process status - Configuration file correctness - Port occupation status - Log error information ``` ### 2. Tool Debugging ``` User: "This tool returns an error, help me find the problem" AI will: 1. Analyze error stack 2. Check input parameters 3. Verify tool logic 4. Provide fix suggestions ``` ### 3. Performance Debugging ``` User: "Server response is slow, help me optimize performance" AI will: 1. Analyze performance bottlenecks 2. Check resource usage 3. Optimize algorithm complexity 4. Add caching mechanisms ``` ## 📚 Learning Resources ### Cursor-Specific Features - **@** symbol: Reference specific files or functions - **Tab completion**: AI-driven code completion - **Cmd+K**: Natural language editing - **Cmd+L**: Chat with AI ### MCP Integration - Use `@mcp` prefix to reference MCP functionality - Call tools directly through Cursor Chat - View MCP server status in real-time ## 🎉 Best Practices ### 1. Effective Prompts ``` ✅ Good prompt: "Create an MCP tool for calculating days between two dates, including input validation and error handling" ❌ Vague prompt: "Make a date tool" ``` ### 2. Incremental Development ``` 1. Create basic functionality first 2. Add error handling 3. Improve documentation 4. Add tests 5. Performance optimization ``` ### 3. Leverage Context ``` User: "Based on the tool just created, create another related tool" AI will understand context and create related functionality ``` ## 🚨 Common Issues ### Q: Cursor cannot recognize MCP server? **Solution:** 1. Check MCP server configuration path 2. Confirm server is running 3. Restart Cursor IDE 4. Check Cursor logs ### Q: AI-suggested code doesn't comply with project standards? **Solution:** 1. Confirm `.cursor/rules` files exist 2. Explicitly mention standard requirements in prompts 3. Use `@rules` to reference specific rules ### Q: How to make AI better understand project structure? **Solution:** 1. Use `@codebase` to reference entire project 2. Mention relevant files in conversation 3. Maintain clear project documentation