Provides real-time weather data and forecasts to AI models and language assistants through an API.
Sponsored
mcp-weather is a lightweight, Python-based server designed to integrate real-time weather data with AI models using the Model Context Protocol (MCP). It allows AI assistants and large language models (LLMs) to access dynamic meteorological information, such as current conditions and multi-day forecasts, by exposing specialized 'tools' that query external weather APIs. The project serves as a practical demonstration of building an MCP server, connecting it to third-party services like OpenWeatherMap, and making that functionality discoverable and usable by any MCP-compatible AI client, thereby enhancing the AI's ability to deliver contextually relevant and up-to-date responses.
Key Features
01Full compatibility with the Model Context Protocol (MCP)
02Multi-Day Weather Forecasts
03Secure API key management via environment variables
040 GitHub stars
05Asynchronous operations for efficient external API requests
06Real-time Weather Queries for global cities
Use Cases
01Integrate dynamic meteorological data into MCP-compatible AI applications.
02Enable AI assistants to answer user questions about current weather conditions.
03Allow LLMs to provide multi-day weather forecasts for specified locations.
