MCP Weather Server

What is MCP Weather Server?

A TypeScript-based server built with the MCP SDK that enables large language models (LLMs) supporting the Model Context Protocol to retrieve real-time weather forecasts and alerts. It acts as middleware between weather data APIs and AI systems, bridging meteorological data sources with language models.

How to use MCP Weather Server?

Clone and build the repository, then add the server configuration to your Claude desktop configuration file (claude_desktop_config.json). Restart the Claude desktop application; your Claude instance will then have access to real-time weather data through MCP.

Key features of MCP Weather Server

• Retrieves real-time weather forecasts for LLMs through function calling
• Enables AI models to access and process weather alerts by location
• Built with TypeScript for type safety and improved developer experience
• Implements the Model Context Protocol for standardized LLM communication
• Integrates seamlessly with the Claude desktop client

Use cases of MCP Weather Server

• An AI assistant incorporating current weather conditions into travel recommendations
• A chatbot providing location-specific weather alerts during emergency preparedness conversations
• A language model generating weather-aware responses without leaving the chat interface

FAQ from MCP Weather Server

What is the transport mechanism used by MCP Weather Server?

The server communicates via the standard input/output (stdio) transport, as shown in the Claude configuration where node is invoked with the server script.

Does MCP Weather Server require an API key for weather data?

The README does not specify authentication or API key requirements. It only documents the server build and configuration steps.

What are the runtime dependencies for MCP Weather Server?

The server is built with TypeScript and requires Node.js to run. The configuration uses the node command to execute the built index.js file.

Can MCP Weather Server be used with LLMs other than Claude?

The README only provides integration instructions for the Claude desktop client. It states the server works with any LLM that supports the Model Context Protocol, but no other clients are explicitly documented.

Where does weather data come from and where does it live?

The README does not name the upstream weather API or describe data storage; it only indicates that the server acts as middleware between weather data APIs and language models.