Summary
A straightforward weather server that wraps the National Weather Service API to pull forecasts and alerts for U.S. locations. You get two tools: one for grabbing active weather alerts by state, another for detailed forecasts by coordinates or location. Built as a homework assignment for MIT's AI Studio course, so it's minimal but functional. The developer added a quirky feature where the LLM can respond in pirate speak if you ask for it, which is more about demonstrating tone control than serious utility. Runs through Smithery's infrastructure, so you'll need an API key from them to deploy it. Good for learning how MCP servers work or prototyping simple weather integrations without setting up your own NWS API calls.
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An MCP server built with Smithery CLI
Functions of the tools that are being connected
This weather app has two functions: get alert and get forecast. Get alert gets any weather alert within the U.S. state, and get forecast gets the weather forecast for that location.
To make things more interesting, if you ask the it to speak in a pirate like tone, it can answer your requests with such a tone.
Prerequisites
- Smithery API key: Get yours at smithery.ai/account/api-keys
Getting Started with running the server
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Run the server:
uv run dev -
Test interactively:
uv run playground
Try saying "Say hello to John" to test the example tool.
Development of the server
Your server code is in src/hello_server/server.py. Add or update your server capabilities there.
Deploying the server
Ready to deploy? Push your code to GitHub and deploy to Smithery:
-
Create a new repository at github.com/new
-
Initialize git and push to GitHub:
git add . git commit -m "Hello world 👋" git remote add origin https://github.com/YOUR_USERNAME/YOUR_REPO.git git push -u origin main -
Deploy your server to Smithery at smithery.ai/new
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Get the MCP →Notes, actions and memory. Without a meeting bot. First month 100% off.
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