MCP Weather Server

MCP Weather Server

Enables AI agents to access real-time and historical weather data through multiple weather APIs including OpenMeteo, Tomorrow.io, and OpenWeatherMap. Provides comprehensive meteorological information including current conditions, forecasts, historical data, and weather alerts.

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README

MCP Weather Server

The MCP Weather Server is a comprehensive Model Context Protocol (MCP) compliant server designed to provide AI agents with access to real-time and historical weather data. Built using Python and FastAPI, it integrates with multiple weather APIs to deliver accurate, up-to-date meteorological information.

Key Features

  • Model Context Protocol (MCP) compliance for seamless AI agent integration
  • Multiple API integration: OpenMeteo, Tomorrow.io, Google Weather (via SerpApi), OpenWeatherMap, and AccuWeather.
  • Comprehensive weather data: current conditions, forecasts, historical data, and alerts
  • Robust error handling and data validation
  • Configurable through environment variables
  • Extensive logging and monitoring capabilities
  • RESTful API design with JSON responses
  • Built-in testing and validation tools

Installation & Setup

Prerequisites

  • Python 3.8 or higher
  • pip package manager
  • Internet connection for API access
  • Optional: Tomorrow.io API key for premium features

Installation Steps

  1. Clone or download the project files
  2. Install dependencies: pip install -r requirements.txt
  3. Copy .env.example to .env
  4. Configure environment variables (optional Tomorrow.io API key)
  5. Run the server: python -m mcp_weather_server.server

Project Structure

mcp-weather-server/
├── src/mcp_weather_server/
│   ├── __init__.py
│   ├── server.py
│   ├── tools/
│   │   ├── __init__.py
│   │   ├── open_meteo.py
│   │   └── tomorrow_io.py
│   └── utils/
│       ├── __init__.py
│       └── weather_utils.py
├── requirements.txt
├── pyproject.toml
├── .env.example
├── README.md
├── test_server.py
└── examples.py

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