Weather MCP Server Overview

The Weather MCP Server provides a lightweight, high‑performance interface for fetching real‑time weather data from the National Weather Service (NWS) API. By exposing two concise tools— and —the server allows AI assistants to retrieve critical weather information without exposing the underlying API keys or handling HTTP requests directly. This abstraction is especially valuable for developers building conversational agents that need to answer weather‑related queries or trigger actions based on severe weather conditions.

Problem Solved

Many AI applications require up‑to‑date meteorological data to offer useful advice or automate responses. Directly integrating with the NWS API can be cumbersome: developers must manage authentication, rate limits, and data parsing. The Weather MCP Server encapsulates these concerns behind a simple, declarative interface. It handles request construction, error handling, and logging internally, freeing developers to focus on higher‑level logic. This reduces boilerplate code and minimizes the risk of exposing sensitive configuration details.

Core Functionality

• Weather Alerts: returns the current weather alerts for any U.S. state identified by its two‑letter code (e.g., “CA” for California). This tool is ideal for applications that need to notify users about impending hazards such as tornadoes, floods, or severe thunderstorms.
• Location‑Based Forecast: fetches a detailed forecast for any geographic coordinate. The response includes temperature, precipitation probability, wind speed, and other key metrics useful for planning outdoor activities or scheduling logistics.

Both tools return structured data that can be directly consumed by an AI assistant, allowing natural language responses to be generated from machine‑readable information.

Key Features

• FastMCP Integration: Built on FastMCP, the server benefits from asynchronous I/O and minimal overhead, ensuring quick response times even under load.
• Configurable Logging: Developers can adjust log levels, formats, and timeouts via , enabling tailored debugging or production‑ready logging.
• Robust Error Handling: Network failures, API errors, and malformed requests are gracefully logged and translated into user‑friendly error messages, preventing crashes in downstream AI workflows.
• Extensibility: The modular design allows additional NWS endpoints (e.g., radar, alerts by ZIP) to be added with minimal effort.

Real‑World Use Cases

• Travel Planning Bots: Provide travelers with up‑to‑date weather forecasts for their destinations, helping them choose suitable activities.
• Emergency Response Systems: Trigger alerts when severe weather conditions are detected in a specific state, enabling timely notifications to affected users.
• Smart Home Automation: Adjust HVAC or irrigation systems based on forecasted temperatures and precipitation probabilities.
• Agricultural Advisory Tools: Deliver weather alerts to farmers, allowing them to protect crops and livestock from impending hazards.

Integration with AI Workflows

In a typical MCP workflow, an AI assistant receives a user query such as “Will it rain in Seattle tomorrow?” The assistant resolves the location to latitude and longitude, then calls . The structured response is passed back to the assistant’s language model, which formats a natural‑language reply. Because the server handles all HTTP communication and error handling, developers can write concise MCP client code without worrying about the intricacies of the NWS API.

Standout Advantages

• Zero‑Code Client Interaction: Developers can invoke weather tools using simple MCP calls, eliminating the need for custom HTTP clients or API wrappers.
• Transparent Configuration: The file exposes all tunable parameters, making it easy to adapt the server for different environments or compliance requirements.
• Open‑Source and MIT Licensed: The project encourages community contributions, ensuring that new features—such as additional forecast granularity or multi‑state alert aggregation—can be added quickly.

Overall, the Weather MCP Server streamlines access to authoritative weather data, enabling AI assistants and developer tools to deliver timely, actionable information with minimal effort.