Weather Information Service MCP Server

@asifdotpy

Basic information

About Weather Information Service MCP Server

No overview available yet

Weather Information Service MCP Server config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "mcp-weather-server-asifdotpy": {
      "command": "python",
      "args": [
        "weather.py"
      ]
    }
  }
}

Weather Information Service MCP Server tools

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.

Overview

What is Weather Information Service?

It fetches weather alerts and forecasts from the National Weather Service (NWS) API, exposing them as tools via the FastMCP framework. It is intended for developers who need to integrate real-time US weather data into their applications.

How to use Weather Information Service?

Install dependencies (e.g., pip install httpx), then run python weather.py to start the FastMCP server. Use the provided tools get_alerts(state) for active alerts and get_forecast(latitude, longitude) for a 5-period forecast.

Key features of Weather Information Service

Fetches active weather alerts for any US state.
Retrieves a 5-period weather forecast for a location.
Uses structured JSON logging with correlation IDs.
Configurable log level and environment variables.
Containerizable via the included Dockerfile.

Use cases of Weather Information Service

Integrate live weather alerts into a monitoring dashboard.
Provide forecast data for travel or event planning.
Automate weather-aware notifications in smart home systems.

Frequently asked questions

What data source does the service use?

It uses the National Weather Service (NWS) API to fetch alerts and forecasts.

How do I run the service?

Run `python weather.py` directly. The service starts a FastMCP server that listens for requests (e.g., via stdio as configured in `smithery.yaml`).

What are the runtime dependencies?

Python 3.x and the `httpx` library. Other dependencies are listed in `pyproject.toml` and can be installed with `pip install .`.

How can I configure logging?

Set the `ENV` environment variable to `production` for JSON logs, or leave it unset for human‑readable output. Use `LOG_LEVEL`, `APP_VERSION`, and `HOSTNAME` to control verbosity, version, and hostname in logs.

What tools does the service expose?

Two tools: `get_alerts(state)` returns active alerts for a US state, and `get_forecast(latitude, longitude)` returns the next five forecast periods for a location.

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