MCP-Creator-MCP

# MCP-Creator-MCP 🚀 **A meta-MCP server that democratizes MCP server creation through AI-guided workflows and intelligent templates.** Transform vague ideas into production-ready MCP servers with minimal cognitive overhead and maximum structural elegance. ## 🎯 Vision Creating MCP servers should be as simple as describing what you want. MCP Creator bridges the gap between idea and implementation, providing intelligent guidance, proven templates, and streamlined workflows. ## ✨ Core Features - **🤖 AI-Guided Creation**: Get intelligent suggestions and best practices tailored to your use case - **📚 Template Library**: Curated collection of proven MCP server patterns - **🔄 Workflow Engine**: Save and reuse creation workflows for consistent results - **🎨 Gradio Interface**: User-friendly web interface for visual server management - **🔧 Multi-Language Support**: Python, Gradio, and expanding language ecosystem - **📊 Built-in Monitoring**: Server health checks and operational visibility - **🛡️ Best Practices**: Automated validation and security recommendations  ## 🚀 Quick Start ### Prerequisites - Python 3.10 or higher - uv package manager - Claude Desktop (for MCP integration) ### Installation ```bash # Clone and set up the project git clone https://github.com/angrysky56/mcp-creator-mcp.git cd mcp-creator-mcp # Create and activate virtual environment uv venv --python 3.12 --seed source .venv/bin/activate # Install dependencies uv add -e . # Configure environment cp .env.example .env # Edit .env with your API keys (see Configuration section) ``` ### Basic Usage #### Option 1: As an MCP Server (Recommended) 1. **Configure Claude Desktop**: ```bash # Copy the example config cp example_mcp_config.json ~/path/to/claude_desktop_config.json # Edit paths and API keys as needed ``` 2. **Start using in Claude Desktop**: - Restart Claude Desktop - Use tools like `create_mcp_server`, `list_templates`, `get_ai_guidance` #### Option 2: Standalone Interface ```bash # Launch the Gradio interface uv run gradio_interface.py # Or use the CLI uv run mcp-creator-gui ``` ## 📖 Configuration ### Environment Variables Create a `.env` file with your settings: ```env # AI Model Providers (at least one required for AI guidance) ANTHROPIC_API_KEY=your_anthropic_key_here OPENAI_API_KEY=your_openai_key_here OLLAMA_BASE_URL=http://localhost:11434 # MCP Creator Settings DEFAULT_OUTPUT_DIR=./mcp_servers LOG_LEVEL=INFO # Gradio Interface GRADIO_SERVER_PORT=7860 GRADIO_SHARE=false ``` ### Claude Desktop Integration 1. **Edit your Claude Desktop config** (usually at `~/.config/Claude/claude_desktop_config.json`): ```json { "mcpServers": { "mcp-creator": { "command": "uv", "args": [ "--directory", "/path/to/mcp-creator-mcp", "run", "python", "main.py" ], "env": { "ANTHROPIC_API_KEY": "your_key_here" } } } } ``` 2. **Restart Claude Desktop** ## 🛠️ Usage Examples ### Creating Your First MCP Server ```python # In Claude Desktop, ask: "Create an MCP server called 'weather_helper' that provides weather data and forecasts" # Or use the tool directly: create_mcp_server( name="weather_helper", description="Provides weather data and forecasts", language="python", template_type="basic", features=["tools", "resources"] ) ``` ### Getting AI Guidance ```python # Ask for specific guidance: get_ai_guidance( topic="security", server_type="database" ) # Or access guidance resources: # Use resource: mcp-creator://guidance/sampling ``` ### Managing Templates ```python # List available templates list_templates() # Filter by language list_templates(language="python") ``` ## 🏗️ Architecture ### Core Principles - **Simplicity**: Each component has a single, clear responsibility - **Predictability**: Consistent patterns reduce cognitive load - **Extensibility**: Modular design enables easy customization - **Reliability**: Comprehensive error handling and graceful degradation ### Component Overview ``` ├── src/mcp_creator/ │ ├── core/ # Core server functionality │ │ ├── config.py # Clean configuration management │ │ ├── template_manager.py # Template system │ │ └── server_generator.py # Server creation engine │ ├── workflows/ # Workflow management │ ├── ai_guidance/ # AI assistance system │ └── utils/ # Shared utilities ├── templates/ # Template library ├── ai_guidance/ # Guidance content └── mcp_servers/ # Generated servers (default) ``` ## 📚 Template System ### Available Templates - **Python Basic**: Clean, well-structured foundation - **Python with Resources**: Database and API integration patterns - **Python with Sampling**: AI-enhanced server capabilities - **Gradio Interface**: Interactive UI with MCP integration ### Creating Custom Templates Templates use Jinja2 with clean abstractions: ```python # Template structure templates/languages/{language}/{template_name}/ ├── metadata.json # Template configuration ├── template.py.j2 # Main template file └── README.md.j2 # Documentation template ``` ## 🔄 Workflow System ### Saving Workflows ```python save_workflow( name="Database MCP Server", description="Complete database integration workflow", steps=[ { "id": "collect_requirements", "type": "input", "config": {"fields": ["db_type", "connection_string"]} }, { "id": "security_review", "type": "ai_guidance", "config": {"topic": "database_security"} }, { "id": "generate_server", "type": "generation", "config": {"template": "python:database"} } ] ) ``` ## 🔧 Development ### Project Structure The codebase follows clean architecture principles: - **Separation of Concerns**: Each module has a single responsibility - **Dependency Injection**: Components are loosely coupled - **Error Boundaries**: Graceful failure handling throughout - **Type Safety**: Comprehensive type hints and validation ### Adding New Templates 1. Create template directory: `templates/languages/{lang}/{name}/` 2. Add `metadata.json` with template configuration 3. Create `template.{ext}.j2` with Jinja2 template 4. Test with the template manager ### Contributing 1. Fork the repository 2. Create a feature branch with descriptive name 3. Follow the existing code patterns and style 4. Add tests for new functionality 5. Submit a pull request with clear description ## 🛡️ Security & Best Practices ### Built-in Protections - **Input Validation**: All user inputs are validated and sanitized - **Process Management**: Proper cleanup prevents resource leaks - **Error Handling**: Graceful failure with helpful messages - **Logging**: Comprehensive operational visibility ### Recommended Practices - Use environment variables for sensitive data - Implement rate limiting for production deployments - Regular security audits of generated servers - Monitor server performance and resource usage ## 🐛 Troubleshooting ### Common Issues **Server won't start:** ```bash # Check dependencies uv add -e . # Verify configuration cat .env # Check logs tail -f logs/mcp-creator.log ``` **Claude Desktop integration:** ```bash # Verify config file syntax python -m json.tool claude_desktop_config.json # Check server connectivity python main.py --test ``` **Template errors:** ```bash # List available templates uv run python -c "from src.mcp_creator import TemplateManager; print(TemplateManager().list_templates())" ``` ## 📊 Monitoring & Operations ### Health Checks The server provides built-in health monitoring: - **Resource usage tracking** - **Error rate monitoring** - **Performance metrics** - **Template validation** ### Logging All operations are logged to stderr (MCP compliance): ```bash # View logs in real-time python main.py 2>&1 | tee mcp-creator.log ``` ## 🚀 What's Next? - **Multi-language expansion**: TypeScript, Go, Rust templates - **Cloud deployment**: Integration with major cloud platforms - **Collaboration features**: Team workflows and template sharing - **Advanced AI**: Enhanced code generation and optimization - **Marketplace**: Community template and workflow ecosystem ## 📝 License MIT License - see [LICENSE](LICENSE) for details. ## 🤝 Contributing We welcome contributions! Please see [CONTRIBUTING.md](CONTRIBUTING.md) for guidelines. ## 💬 Support - **Issues**: [GitHub Issues](https://github.com/angrysky56/mcp-creator-mcp/issues) - **Discussions**: [GitHub Discussions](https://github.com/angrysky56/mcp-creator-mcp/discussions) - **Documentation**: [Wiki](https://github.com/angrysky56/mcp-creator-mcp/wiki) --- **Built with ❤️ for the MCP community** *MCP Creator makes sophisticated AI integrations accessible to everyone, from hobbyists to enterprise teams.*