🌩️ MCP Weather Alerts Tool using FastMCP + Claude Desktop

Created By
nahilahmeda year ago
A Python MCP (Model Context Protocol) server that fetches real-time weather alerts by U.S. state using api.weather.gov, built with FastMCP and integrated into Claude Desktop.
Overview

What is MCP Weather Alerts Tool?

The MCP Weather Alerts Tool is a Python-based application that utilizes the Model Context Protocol (MCP) to fetch real-time weather alerts for U.S. states using the api.weather.gov API, integrated with Claude Desktop for enhanced user interaction.

How to use MCP Weather Alerts Tool?

To use the tool, set up the MCP server with the provided instructions, and then interact with it through Claude Desktop by asking for weather alerts for a specific state.

Key features of MCP Weather Alerts Tool?

  • Real-time weather alerts retrieval by U.S. state.
  • Integration with Claude Desktop for AI-assisted queries.
  • Structured output including event, severity, description, and instructions.
  • Interactive testing via MCP Inspector.

Use cases of MCP Weather Alerts Tool?

  1. Fetching weather alerts for emergency preparedness.
  2. Integrating with AI assistants for user-friendly weather inquiries.
  3. Providing structured weather information for applications and services.

FAQ from MCP Weather Alerts Tool?

  • Can I get alerts for any U.S. state?
    Yes, you can request alerts for any state by specifying the state code (e.g., 'TX' for Texas).

  • Is the tool free to use?
    Yes, the MCP Weather Alerts Tool is open-source and free to use.

  • How accurate are the weather alerts?
    The tool retrieves alerts directly from the official weather service, ensuring high accuracy.

Project Info
Created At
a year ago
Updated At
a year ago
Author Name
nahilahmed
Star
0
Language
Python
License
-

Recommend Servers

View All
Mnemom

14 hours ago
//beforeyouship — LLM Cost Modeling From Your Editor
@Indiegoing

Query realistic LLM cost models without leaving your editor. beforeyouship models the **true monthly cost** of an LLM app architecture — retries, prompt caching, batch discounts, infra overhead, and 3×/10× growth — across GPT-5.x, Claude, Gemini, DeepSeek, and more. Not a token calculator: a planning tool for the design phase, before you commit to a stack. **No API key needed to try it** — demo mode covers the six free-tier models. A Pro key from [beforeyouship.dev](https://beforeyouship.dev) unlocks the full 18-model catalog. ## What you can ask - "How much will a RAG chatbot cost at 10,000 requests/day?" - "Compare Claude Haiku vs Gemini Flash pricing for my workload" - "What's the cheapest model for a multi-step agent at scale?" - "Show me current per-token prices for Anthropic models" ## Tools ### `estimate_cost` Full cost model for an architecture at a given usage level. Returns Naive / Realistic / Worst Case monthly cost per model, 3×/10× growth scenarios, and an opinionated recommendation with reasoning. ### `get_model_prices` Current per-1M-token pricing — input, output, cached input, batch — with context windows and staleness metadata. ### `list_archetypes` Seven preset architecture patterns (simple chatbot, chatbot with history, RAG pipeline, multi-model router, coding assistant, document processor, multi-step agent) used as starting points for estimates. ## Setup **Claude Code:** ​```bash claude mcp add --transport http beforeyouship https://beforeyouship.dev/api/mcp ​``` **Cursor / other clients** — add a remote server: ​```json { "mcpServers": { "beforeyouship": { "type": "streamable-http", "url": "https://beforeyouship.dev/api/mcp" } } } ​``` Add an `Authorization: Bearer bys_...` header with a Pro key for the full catalog. ## Try it > Estimate the monthly cost of a RAG pipeline at 10,000 requests/day

13 hours ago
Docwand

13 hours ago