What are the prerequisites?
Python 3.8+ and a free API key from OpenWeatherMap.
@jdhettema
基本信息
An MCP server that connects AI assistants to real-time weather data through OpenWeatherMap API using Server-Sent Events.
使用下面的配置,将此服务器添加到你的 MCP 客户端。
{
"mcpServers": {
"mcp-weather-sse": {
"command": "python",
"args": [
"-m",
"venv",
"venv"
]
}
}
}工具列表暂未提供
当前收录暂时没有可展示的工具列表,不代表服务没有工具。请查阅项目文档了解支持的能力。
工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。
It is a Model Context Protocol (MCP) server that connects to the OpenWeatherMap API via Server-Sent Events (SSE) to provide real-time weather data to AI tools like Claude, CursorAI, and MCP-Inspector.
Install the server, create a virtual environment, and install dependencies (pip install mcp requests). Start it with your OpenWeatherMap API key using a command-line argument (--api-key) or the OPENWEATHER_API_KEY environment variable. Then configure your MCP client (e.g., Cursor AI, Claude Desktop) to connect to the SSE endpoint at http://127.0.0.1:3001/sse.
Python 3.8+ and a free API key from OpenWeatherMap.
Run `python mcp_weather_sse.py --api-key YOUR_API_KEY` or export `OPENWEATHER_API_KEY` and run without the flag. Customize host/port with `--host` and `--port`.
Claude Desktop, Cursor AI, and MCP-Inspector are explicitly supported.
Three tools: `get_current_weather` (by city), `get_weather_forecast` (city + days), and `get_weather_by_coordinates` (latitude/longitude).
The server binds to 127.0.0.1 by default. For production, you should implement authentication, HTTPS, and rate limiting to protect your OpenWeatherMap API quota.

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