Python Weather
Provides real-time weather data for specified locations via an AI agent-accessible tool built with the Model Context Protocol (MCP).
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This project serves as a tutorial demonstrating how to construct a simple weather server using the Model Context Protocol (MCP). It integrates with the OpenWeatherMap API to fetch current weather conditions for any given location and exposes this functionality as a tool accessible by AI agents (LLMs). The server automatically generates a JSON schema for its `get_weather` function, enabling AI agents to understand and invoke its capabilities seamlessly. The tutorial covers essential setup steps, API key management, and deployment for interaction with various MCP clients, including popular AI assistants like Claude Desktop.
Características Principales
- Includes a browser-based inspector for easy testing and debugging of the MCP server.
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- Exposes weather functionality as an AI agent-accessible tool via MCP.
- Automatically generates JSON schema for AI agent tool invocation from function signatures.
- Fetches real-time weather data using the OpenWeatherMap API.
- Demonstrates integration and setup with popular MCP clients like Claude Desktop.
Casos de Uso
- Enabling AI agents (LLMs) to retrieve current weather conditions for specific locations.
- Serving as a foundational example for developers to build custom MCP tools for various data sources.
- Integrating real-time external data and services into AI agent workflows.
