"How to break tasks into smaller steps" matching MCP servers:

Enables AI to read live weather data and manage a persistent to-do list through MCP tools, demonstrating both read and write capabilities without API keys.

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.

Enables scheduling of construction works against weather forecasts, using deterministic tools to check weather suitability, estimate curing times, and place dependent tasks into the earliest non-prohibited time windows.

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.

Model Context Protocol server: plug AEMET into Claude Desktop, Cursor, Windsurf or any MCP client. Runs locally over stdio.

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

Archives Garmin Connect health data locally (steps, HR, sleep, body battery) as JSON, no cloud, and also pulls context data (weather, pollen, air quality). Built-in MCP server (with SQLite cache) exposes the archive for querying via LLM tool calls.

Enables an AI assistant to manage personal tasks in SQLite, answer questions from a local SQLite database through bounded read-only queries, and retrieve weather forecasts from Open-Meteo.

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.

Enables AI assistants to fetch real-time weather data, forecasts up to 10 days, and compare weather conditions between cities using WeatherAPI.com with support for both Celsius and Fahrenheit units.

Enables users to work out soil, mulch, compost, topsoil and potting mix volumes and bag counts for beds and pots, compare bagged versus bulk costs at their own prices, check what to sow each month, and see how often a town has had frost after Melbourne Cup Day. It runs as a read-only, stateless MCP server that connects directly inside Claude, ChatGPT, Cursor and VS Code.

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

Enables agents to retrieve live planetary risk intelligence—space weather, earthquakes, and wildfires—fused into a deterministic Instability Index, along with sealed briefing and integrity verification tools.

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 agents to pull live overnight forecasts for grower blocks and score frost risk with an itemised, versioned engine, returning cold-window start/end hours and a run-protection, stand-by, or no-action verdict. It also lets agents list blocks and sheets, create or update idempotent decision records, and replay their SHA-384 hash chain to verify nothing was altered.