MCP Project Initializer

# MCP Project Initializer An intelligent MCP (Model Context Protocol) server that automates the setup of new AI-powered MCP server development projects. This tool acts as a conversational guide through any standard MCP client to set up projects with necessary context, rules, and documentation for AI-assisted development. ## Features - 🤖 **Conversational Project Setup** - Interactive step-by-step project initialization - 📋 **AI-Enhanced PRD Generation** - Transform basic concepts into comprehensive specifications - 🔧 **Technology-Specific Context** - Automatically downloads SDK documentation and best practices - 📚 **Development Rules Integration** - Includes coding standards and AI-optimized guidelines - 🎯 **Context-Based Development** - Prepares projects for AI agents to implement with creativity - 🛡️ **MCP Protocol Compliant** - Full compatibility with MCP clients and standards ## Quick Start ### Installation ```bash # Clone the repository git clone <repository-url> cd mcp-initializer # Install dependencies npm install # Build the project npm run build ``` ### Using with MCP Clients #### Windsurf IDE Configuration Add this server to your Windsurf MCP settings: ```json { "mcpServers": { "mcp-project-initializer": { "command": "node", "args": ["/path/to/mcp-initializer/build/index.js"], "description": "AI-powered project initialization server" } } } ``` #### Generic MCP Client Configuration For any MCP client that supports STDIO transport: ```json { "name": "mcp-project-initializer", "command": "node", "args": ["/path/to/mcp-initializer/build/index.js"], "transport": "stdio" } ``` ## Usage ### Starting a New Project 1. **Start the conversation**: Use the `start_mcp_project` tool 2. **Set project name**: Use `set_project_name` with your desired project name 3. **Choose directory**: Use `set_project_directory` with an absolute path 4. **Select technology**: Use `set_project_technology` (typescript or python) 5. **Provide concept**: Use `set_project_description` with a high-level overview 6. **Add documentation** (optional): Use `add_project_documentation` for additional context 7. **Setup foundation**: Use `setup_project_foundation` to create the project structure 8. **Generate context**: Use `generate_mcp_server` to prepare for AI implementation ### Example Conversation Flow ``` User: Use start_mcp_project AI: 🚀 Welcome! I'll help you create a new MCP Server project... User: Use set_project_name with "task-manager-mcp" AI: ✅ Great! Project name set to: task-manager-mcp... User: Use set_project_directory with "/Users/yourname/Projects" AI: ✅ Perfect! Project directory set... User: Use set_project_technology with "typescript" AI: ✅ Excellent! Technology set to: typescript... User: Use set_project_description with "Help users manage daily tasks with reminders" AI: ✅ Perfect! Description captured... User: Use setup_project_foundation AI: 🚀 Setting up project foundation... ✓ Downloaded essential MCP documentation... User: Use generate_mcp_server AI: 🎉 Your Project is Ready for AI Implementation! ``` ## Project Structure Created When you run the MCP Project Initializer, it creates: ``` your-project/ ├── README.md # Project overview ├── CLAUDE.md # AI development guidance ├── IMPLEMENTATION.md # Detailed implementation guide ├── PRD.md # Product Requirements Document ├── package.json # Dependencies and scripts ├── tsconfig.json # TypeScript configuration ├── .gitignore # Git ignore rules ├── .windsurf/ │ └── rules/ # Development best practices │ ├── general.md # General coding standards │ ├── typescript.md # TypeScript-specific rules │ └── mcp.md # MCP development patterns ├── docs/ │ └── external/ # Downloaded documentation │ ├── llms-full.txt # MCP client compatibility │ └── typescript-sdk-README.md # SDK documentation ├── src/ # Source code directory └── tests/ # Test directory ``` ## Key Features ### AI-Enhanced Development - **Context-Rich Setup**: Downloads essential MCP documentation automatically - **Best Practices Integration**: Includes technology-specific coding standards - **PRD Enhancement**: AI agents expand basic concepts into detailed specifications - **Step-by-Step Guidance**: Clear implementation instructions for AI agents ### Technology Support - **TypeScript**: Full Node.js MCP server setup with ES modules - **Python**: Complete Python MCP server configuration - **Extensible**: Easy to add support for additional technologies ### MCP Protocol Compliance - **Tools-Only Design**: No prompts - fully compatible with tools-only clients - **Conversational State**: Maintains conversation flow across tool calls - **Error Handling**: Comprehensive validation and user guidance - **Standard Transport**: Uses STDIO for maximum compatibility ## Development ### Building from Source ```bash # Install dependencies npm install # Build the project npm run build # Run in development mode npm run dev # Type checking npm run typecheck # Linting npm run lint ``` ### Project Structure ``` mcp-initializer/ ├── src/ │ ├── index.ts # MCP server main entry │ ├── project-initializer.ts # Core initialization logic │ └── types.ts # TypeScript type definitions ├── templates/ │ └── rules/ # Development rule templates │ ├── typescript.md # TypeScript best practices │ └── python.md # Python best practices ├── build/ # Compiled output └── docs/ # Project documentation ``` ## Requirements - **Node.js**: >= 18.0.0 - **MCP Client**: Any MCP-compatible client (Windsurf, Claude Desktop, etc.) - **Operating System**: macOS, Linux, Windows ## Contributing 1. Fork the repository 2. Create a feature branch 3. Make your changes following the coding standards 4. Test with a real MCP client 5. Submit a pull request ## License MIT License - see LICENSE file for details. ## Support For issues and questions: - Check the documentation in `/docs` - Review the generated `IMPLEMENTATION.md` for guidance - Open an issue on the project repository --- **Ready to create AI-powered projects?** Configure this MCP server in your client and start building! 🚀