"Comment perdre du poids (How to lose weight)" matching MCP servers:

Enables travel-related queries and planning including weather, train and flight information, itinerary generation, and travel knowledge retrieval via RAG, using an AI agent with MCP protocol.

Solar vitamin D: whether the sun where you are can make vitamin D right now, how many minutes your Fitzpatrick skin type needs for a target dose, which months of the year synthesis is possible at your latitude, and how much a sun session produced. Computed from solar geometry, a clear-sky UV model with ozone and altitude, and live Open-Meteo UV data.

Tracks how long you've been indoors, nags you to touch grass, detects frustration, and recommends nearby parks with live weather.

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.

Enables AI agents to fetch real-time weather data for any location using the OpenWeatherMap API. Demonstrates how to build a simple MCP server that exposes weather information as a tool for LLMs.

An MCP server that provides web search capabilities through the Tavily API and weather data retrieval tools. It demonstrates how to integrate external APIs into AI applications and build agentic workflows with LangGraph.

Provides real-time weather information and multi-day forecasts using the Open-Meteo API through a robust, enterprise-grade architecture. It enables AI assistants to retrieve current conditions, 7-day forecasts, and contextual weather data for any location.

Demonstrates how to integrate Model Context Protocol with Server-Sent Events (SSE) in a FastAPI web application, including a weather service example with tools for getting forecasts and alerts.

Enables users to produce explainable UK garden watering recommendations as deterministic millimetres, litres and runtime from self-reported garden details or an optional postcode, without controlling irrigation hardware.

Wraps the Tomorrow.io Weather API to provide weather data, allowing AI agents to query forecasts and historical conditions via natural language.

A minimal Express-based MCP server that exposes a weather tool through HTTP endpoints, demonstrating how to implement the Model Context Protocol with streamable HTTP transport.

Enables AI assistants to list demo inverter sites, inspect production, pull weather context, and get deterministic panel-cleaning recommendations over MCP using synthetic solar operations data.

Enables LLMs to retrieve 24-hour weather forecasts and city information through natural language queries using city names or coordinates.

Provides real-time NOAA space weather data (solar flares, Kp index, solar wind) and analyzes HF radio propagation conditions for amateur radio operators to determine optimal frequency bands.

A server for querying surf spot data and searching spots, with tools to list regions, spots, get spot info, find spots by criteria, and get mock forecasts.

Enables LLMs to fetch real-time weather data for any city and perform basic arithmetic operations like addition.

An MCP server that generates random numbers by using national weather data as entropy seeds. It provides a unique way to generate random values through weather API integration within the Model Context Protocol.

A server that integrates the MCP library with OpenAI's API, allowing users to interact with various tools, such as the weather tool, through natural language queries.

Demo MCP server that provides weather data for cities, with tools to get weather and list available cities.

A Model Context Protocol server that enables users to fetch weather forecasts through Cursor AI by using natural language queries.