muminfarooq190/Weather
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This document provides a structured overview of a Model Context Protocol (MCP) server designed to expose tools and connect to an MCP host like Claude for Desktop.
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.