"weather" matching MCP servers:

A simple MCP server that provides weather tools, deployable with Docker, and designed to be used with Claude Desktop via a WSL bridge.

A Model Context Protocol (MCP) server built with the mcp-framework to provide weather-related tools and data to AI clients. It enables integration of weather capabilities and custom tools into the MCP ecosystem for use with platforms like Claude Desktop.

A step-by-step workshop for building an MCP server that provides weather tools to AI agents, enabling secure API key usage.

A simple service using Model Context Protocol (MCP) to provide weather information for multiple cities including Fukuoka, Tokyo, Osaka, Moscow, and New York.

A simple MCP server demonstrating tools, resources, and prompts for weather data, built during an Agentic AI Internship.

Demonstrates creating and connecting an MCP weather server using FastMCP, with support for integration with Claude Desktop, Cursor, and local LLMs to query weather alerts and information.

A learning project demonstrating how to build MCP servers with Python, featuring weather query tools that showcase custom tool creation, configuration, and integration with AI assistants.

A basic MCP server adapted from the official quickstart guide that provides weather data functionality and works with OpenAI chat completions API. Demonstrates MCP server setup with configuration examples for Claude Desktop and development tools.

A simple educational MCP server implemented in Node.js that allows users to fetch weather information for cities using the Open-Meteo API.

A template MCP server that provides weather forecasting functionality by fetching current and hourly temperature data from the Open Meteo API for any given latitude and longitude coordinates.

Provides weather information through MCP tools integrated with a FastAPI backend, enabling users to query current weather for single or multiple cities and check API health status.

A tutorial-based MCP server that fetches real-time weather data from the OpenWeatherMap API for specified locations. It serves as a practical example for implementing the Model Context Protocol using Python and the FastMCP library.

Enables deploying a stateless remote MCP server on Cloudflare Workers without authentication, with tools that can be connected to Cloudflare AI Playground or local clients via mcp-remote.

Provides real-time weather data from Open-Meteo API, mathematical calculations, and time zone information through MCP protocol. Works with both Claude Desktop and Gemini AI CLI for natural language interactions.

A local, no-auth MCP server that exposes mocked weather forecast and supported cities tools over Streamable HTTP, enabling developers to test MCP integration with hosts like ChatGPT, Claude, and MCP Inspector.

Claude Code plugin and MCP server that nudges you to take outdoor breaks based on local weather, sunset timing, and session streaks. Exposes check_grass_conditions, suggest_activity, log_touch_grass, and get_stats tools — fully local, no API keys, no cloud storage.

A learning-focused MCP server that provides tools for current time, arithmetic, random quotes, mock weather, and UUID generation, demonstrating the Model Context Protocol end-to-end.

A comprehensive MCP server and client implementation in Python exposing tools (calculator, string utilities, simulated weather), resources (file reader, system info), and prompts (code review, summarization) with security hardening and full configuration management.

A minimal MCP server demo written without the MCP Python SDK that demonstrates the complete protocol flow. It provides weather, file search, and datetime tools, and includes a CLI client that bridges MCP tools with OpenAI function calling.

A beginner-friendly MCP server built in plain Node.js/JavaScript that exposes five tools (calculator, UUID generator, read notes, get weather, password generator) to teach how the Model Context Protocol works under the hood.