MCP Weather Server

The MCP Weather Server is a lightweight, Node‑based service that exposes real‑time weather data to AI assistants through the Model Context Protocol. By wrapping the AccuWeather API, it turns raw meteorological information into a set of well‑structured tools that language models can invoke on demand. This eliminates the need for developers to build custom weather integrations from scratch, allowing assistants to answer location‑specific queries with up‑to‑date forecasts and historical data.

At its core, the server offers two primary tools: and . The hourly tool returns a 12‑hour forecast for any city or coordinate, while the daily tool provides up to 15 days of weather outlooks. Both tools support metric or imperial units, making the data immediately useful for a global user base. Because the server translates AccuWeather responses into clean JSON, LLMs can parse and display temperature, precipitation probability, wind speed, and other key metrics without additional post‑processing.

For developers building AI workflows, the MCP Weather Server plugs directly into any MCP‑compatible client—Claude Desktop, SuperGateway, or custom orchestrators. A simple configuration entry launches the server as a subprocess and injects the required API key, after which the assistant can call or as part of its reasoning chain. This seamless integration means developers can enrich conversational agents with factual weather data, schedule reminders based on upcoming conditions, or generate travel itineraries that account for climate.

Real‑world scenarios abound: a travel assistant can suggest the best days to visit outdoor attractions; a smart home controller can adjust HVAC settings based on forecasted temperatures; or a logistics planner can route deliveries to avoid heavy rain. The server’s low latency and stateless design make it suitable for high‑volume use cases, while the AccuWeather free tier ensures that hobbyists and prototypes can run without upfront costs.

Unique advantages include the server’s adherence to MCP best practices—exposing resources, tools, and prompts in a single, self‑contained package—and its straightforward environment variable configuration. By abstracting away API authentication and rate‑limiting concerns, the MCP Weather Server lets developers focus on higher‑level logic, confident that their AI assistant can reliably fetch accurate weather data whenever needed.