Weather Information Service
@asifdotpy
About Weather Information Service
No overview available yet
Config
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"mcp-weather-server-asifdotpy": {
"command": "python",
"args": [
"weather.py"
]
}
}
}Tools
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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.
FAQ from Weather Information Service
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.
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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