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unofficial-nmw-mcp-server

v1.0.1

Published

unofficial MCP Server base on the National Weather Service API

Readme

National Weather Service MCP Server

This project is an MCP (Model Context Protocol) server that provides weather data using the National Weather Service (NWS) API.

This is not an official NWS product. It is a custom implementation designed to integrate with MCP clients like Claude or OpenAI.

Features

  • Get weather alerts for a US state
  • Get weather forecast for a specific location (latitude/longitude)

Requirements

  • Node.js (v18+ recommended)
  • npm

Installation

  1. Clone the repository:
git clone https://github.com/Lil-Code30/nws-mcp-server.git
cd nws-mcp-server
  1. Install dependencies:
npm install

Build

Compile the TypeScript code:

npm run build

Usage

Run the MCP server:

npm start

The server runs via stdio and exposes two tools:

1. get_alerts

  • Description: Get weather alerts for a US state.
  • Input:
    • state: Two-letter state code (e.g., CA, NY)
  • How it works:
    • Uses the NWS Alerts endpoint: /alerts?area={STATE}
    • Example: https://api.weather.gov/alerts?area=CA
    • Returns active alerts or a message if none are found.

2. get-forecast

  • Description: Get weather forecast for a location.
  • Input:
    • latitude: Latitude of the location (US only)
    • longitude: Longitude of the location (US only)
  • How it works:
    • Uses the NWS Points endpoint: /points/{lat},{lon}
    • Example: https://api.weather.gov/points/37.7749,-122.4194
    • Retrieves the forecast URL from the points response, then fetches forecast data from that URL.
    • Returns a formatted forecast for the location.

NWS API Reference

Notes

  • Only US locations are supported by the NWS API.
  • The server is designed for integration with MCP clients.

Integrating with Claude or Other MCP Clients

You can connect this MCP server to any MCP-compatible client (like Claude, OpenAI, or custom apps) using the Model Context Protocol. The server communicates via stdio, so you can run it locally and connect via a tool or agent interface.