What are the dependencies and runtime requirements?
Python 3.8 or higher, an OpenAI API key (`OPENAI_API_KEY`), and dependencies installed via `uv sync`.
@brunolnetto
基本信息
A MCP server for weather forecast
使用下面的配置,将此服务器添加到你的 MCP 客户端。
{
"mcpServers": {
"weather_mcp": {
"command": "uv",
"args": [
"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。
Weather-MCP is a FastAPI server that integrates with FastMCP and Pydantic AI to provide real-time weather alerts and forecasts for U.S. locations. It is designed for developers who want to enable natural language weather queries in their AI applications.
Clone the repository, set up a virtual environment with uv, install dependencies, and set the OPENAI_API_KEY environment variable. Start the server with python weather_server.py – it runs at http://localhost:8000/sse. Interact via a Pydantic AI agent (e.g., agent.run("Are there any weather alerts for California?")) or directly through the FastMCP client.
34.05, -118.25.Python 3.8 or higher, an OpenAI API key (`OPENAI_API_KEY`), and dependencies installed via `uv sync`.
The README does not specify the underlying weather data provider; it fetches alerts and forecasts for U.S. locations only.
The server itself does not require authentication. It uses the OpenAI API key to power the LLM used for natural language interaction.
No limits are documented in the README. The tools currently cover U.S. weather alerts and forecasts by coordinates.
The server exposes a Server-Sent Events (SSE) endpoint at `http://localhost:8000/sse`.
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