README.md•9.22 kB
# 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)
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**Built with ❤️ for the MCP community**
*MCP Creator makes sophisticated AI integrations accessible to everyone, from hobbyists to enterprise teams.*
