XiaoAI_mapMCP

# XiaozhiMCP-MapNAVI | MCP Map Navigation Tool A powerful MCP tool that integrates with Amap API services, allowing AI to access geographic information, weather data, and route planning. A powerful MCP tool that integrates with Amap API services, allowing AI to access geographic information, weather data, and route planning.   ## Overview | Overview MCP-MapNAVI is based on the Model Context Protocol (MCP), which allows AI language models to interact with external map services. Through this tool, AI can geocode addresses, check weather information, and plan driving routes - extending its capabilities beyond text generation. MCP-MapNAVI is based on the Model Context Protocol (MCP), which allows AI language models to interact with external map services. Through this tool, AI can geocode addresses, check weather information, and plan driving routes - extending its capabilities beyond text generation. ## Features | Features - 🗺️ **Geocoding** - Convert addresses into latitude and longitude coordinates - 🌤️ **Weather Query** - Obtain weather information for specific cities or regions - 🚗 **Driving Route Planning** - Plan driving routes between two points - 🔄 **Automatic Reconnection** - WebSocket connection recovery mechanism with exponential backoff - 🔒 **Secure Communication** - Secure data transmission via WebSocket ## Quick Start | Quick Start 1. Install dependencies: ```bash pip install -r requirements.txt ``` 2. Set up environment variables: ```bash export MCP_ENDPOINT=<your_mcp_endpoint> ``` 3. Run the map_navi example: ```bash python mcp_pipe.py map.py ``` ## Project Structure | Project Structure - `mcp_pipe.py`: Main communication pipe that handles WebSocket connections and process management - `calculator.py`: Example MCP tool implementation for mathematical calculations - `requirements.txt`: Project dependencies ## Creating Your Own MCP Tools | Creating Your Own MCP Tools Here's a simple example of creating an MCP tool: ```python from mcp.server.fastmcp import FastMCP mcp = FastMCP("YourToolName") @mcp.tool() def your_tool(parameter: str) -> dict: """Tool description here""" # Your implementation return {"success": True, "result": result} if __name__ == "__main__": mcp.run(transport="stdio") ``` ## Use Cases | Use Cases - Mathematical calculations - Email operations - Knowledge base search - Remote device control - Data processing - Custom tool integration ## Requirements | Requirements - Python 3.7+ - websockets>=11.0.3 - python-dotenv>=1.0.0 - mcp>=1.8.1 - pydantic>=2.11.4 ## Contributing | Contributing Contributions are welcome! Please feel free to submit a Pull Request. Contributions are welcome! Please feel free to submit a Pull Request. ## License | License This project is licensed under the MIT License - see the LICENSE file for details. This project is licensed under the MIT License - see the LICENSE file for details. ## Acknowledgments | Acknowledgments - Thanks to all contributors who have helped shape this project - Inspired by the need for extensible AI capabilities