MCPeasy

# Custom Tool Template This template provides a starting point for creating custom MCP tools. ## Quick Start 1. **Copy this template** to your custom tools folder inside src/tools/ e.g. src/tools/yourname/yourtoolname/ 2. **Replace placeholders** in `tool.py`: - `TOOL_NAME` → your actual tool name (lowercase, no spaces) - `TOOL_NAMETool` → your tool class name (PascalCase) - Update `description` with what your tool does 3. **Implement the `execute` method** with your tool logic 4. **Update configuration schema** if your tool needs configuration 5. **Test your tool** before committing ## Tool Structure ``` your_tool_name/ ├── __init__.py # Package initialization ├── tool.py # Main tool implementation └── README.md # This documentation ``` ## Configuration If your tool needs configuration (API keys, URLs, etc.), implement `get_config_schema()`: ```python @classmethod def get_config_schema(cls) -> Optional[Dict[str, Any]]: return { "type": "object", "properties": { "api_key": {"type": "string", "description": "Your API key"} }, "required": ["api_key"] } ``` ## Available Dependencies These dependencies are already available in mcpeasy: - `requests` - HTTP client - `sqlalchemy` - Database ORM - `pydantic` - Data validation - `fastapi` - Web framework - `asyncio` - Async programming - `logging` - Logging utilities ## Adding New Dependencies If you need additional dependencies: 1. **Add to this directory's `requirements.txt`**: ``` stripe==5.4.0 pandas>=1.5.0,<2.0.0 ``` 2. **Import with graceful fallback**: ```python try: import stripe except ImportError: stripe = None # Handle missing dependency ``` 3. **Use specific versions** to avoid conflicts 4. **Keep dependencies minimal** - prefer existing mcpeasy dependencies when possible 5. **Test the Docker build** to ensure dependencies install correctly ## Example Implementation ```python async def execute(self, arguments: Dict[str, Any], config: Dict[str, Any] = None) -> ToolResult: try: # Extract arguments text = arguments.get("text", "") # Use configuration api_key = config.get("api_key") if config else None # Process with existing dependency import requests response = requests.post( "https://api.example.com/process", json={"text": text}, headers={"Authorization": f"Bearer {api_key}"} ) # Return structured JSON data (recommended) return ToolResult.json(response.json()) # Or return plain text: # return ToolResult.text(f"Processed: {response.text}") except Exception as e: return ToolResult.error(f"Processing failed: {str(e)}") ``` ## Testing Test your tool locally before deployment: ```python # In your development environment from your_org.tools.your_tool.tool import YourToolTool tool = YourToolTool() result = await tool.execute({"text": "test"}, {"api_key": "test_key"}) print(result) ``` ## Next Steps 1. Implement your tool logic 2. Put code into src/tools/{yourorg}/{yourtool} and don't forget to enable in .env (unless you are using TOOLS='__all__') 3. Test in development environment 4. Deploy and enable for specific clients via admin UI