What data source does the server use?
It fetches weather data from the National Weather Service API.
@bittush8789
Basic information
Creating MCP (Model Context Protocol) weather-related projects involves setting up an MCP server that can fetch and provide weather data.
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"mcp-bittush8789": {
"command": "uv",
"args": [
"run",
"weather.py"
]
}
}
}Tool list not available yet
This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.
We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.
The Weather MCP Server fetches weather data from the National Weather Service API. It provides two tools: get_alerts for active weather alerts in a US state and get_forecast for a short-term forecast at a given latitude/longitude. It is intended for developers using the Model Context Protocol (MCP) framework.
Install dependencies using uv add mcp[cli] httpx requests, then run the server with uv run weather.py. The server communicates via standard I/O. For MCP client integration, add a configuration entry to your config.json specifying the path to uv and the project directory.
get_alerts(state) returns active weather alerts for a US state.get_forecast(latitude, longitude) returns a short-term forecast.It fetches weather data from the National Weather Service API.
The server offers `get_alerts(state)` for alerts and `get_forecast(latitude, longitude)` for forecasts.
Python 3.7 or later, the httpx library, and the MCP framework package `mcp[cli]`.
Add an entry to your client’s `config.json` with the command set to your `uv` binary and arguments including `--directory`, the project path, `run`, and `weather.py`.
The server communicates over standard I/O (stdio).

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