Skip to main content
Glama

Weather MCP Server

We’ll build a server that exposes two tools: get_alerts and get_forecast. Then we’ll connect the server to an MCP host (in this case, Claude for Desktop): Core MCP Concepts MCP servers can provide three main types of capabilities: Resources: File-like data that can be read by clients (like API responses or file contents) Tools: Functions that can be called by the LLM (with user approval) Prompts: Pre-written templates that help users accomplish specific tasks

Prerequisite knowledge This quickstart assumes you have familiarity with: Python LLMs like Claude ​ Logging in MCP Servers When implementing MCP servers, be careful about how you handle logging: For STDIO-based servers: Never write to standard output (stdout). This includes: print() statements in Python console.log() in JavaScript fmt.Println() in Go Similar stdout functions in other languages Writing to stdout will corrupt the JSON-RPC messages and break your server. For HTTP-based servers: Standard output logging is fine since it doesn’t interfere with HTTP responses. ​ Best Practices Use a logging library that writes to stderr or files.

-
security - not tested
F
license - not found
-
quality - not tested

Enables users to get weather alerts and forecasts through natural language interactions. Provides real-time weather information and alert notifications via MCP tools.

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/muminfarooq190/Weather'

If you have feedback or need assistance with the MCP directory API, please join our Discord server