"Understanding and Building Probability Density Functions (PDF) Models" matching MCP servers:

Hosts MCP tools for weather queries and On-Behalf-Of flow, enabling Copilot to retrieve weather data and user info via Azure Functions.

A local MCP server that integrates FastMCP with OpenAI to enable natural language queries for current weather, forecasts, and currency conversion using ExchangeRate-API and Open-Meteo.

Predicts the likelihood of school closures due to snowfall and severe winter weather using real-time weather data and machine learning algorithms.

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.

An MCP server that provides real-time weather alerts, forecasts, stock market data, and news information through various API integrations.

Provides access to Hong Kong climate and weather data from the Hong Kong Observatory, including current conditions, forecasts, warnings, tides, and more.

Enables real-time weather lookup for any location via MCP, returning concise summaries from wttr.in.

Demonstrates OAuth2/OIDC authentication for MCP servers using Asgardeo, with JWT validation and a sample weather tool to showcase secured API access.

Enables AI models to access Swiss weather and climate data from MeteoSwiss, including current observations, forecasts, and warnings.

Enables on-demand weather queries for up to three named locations via Open-Meteo, supporting current conditions, forecasts, rain probability, and conversational location management in English or Japanese.

Enables language models to fetch weather forecasts for Israeli cities by automating a real browser with Playwright to interact with weather2day.co.il, including entering a city, selecting it from autocomplete, and extracting the forecast content.

MCP server connecting AI models to SRG SSR public APIs – weather, TV/radio metadata, program guide and Swiss votations/elections since 1900.

Provides calibrated weather probability signals for Kalshi prediction markets by combining dual-model forecasting (NWS + GFS ensemble) to identify mispriced temperature markets. Enables AI agents to access bias-corrected forecasts and edge signals for weather prediction market intelligence.

Enables riders to ask an assistant for wind-sport forecasts at a named spot, combining AROME, ICON, ECMWF, GFS, UKMO and other models into one hourly table with consensus, spread, gust diagnosis, and onshore/offshore safety relative to the beach orientation. It also finds spots, lists which models apply locally, and returns rideable daytime windows within a given knot range.

A simple server that implements the Model Context Protocol, allowing AI models like Claude to fetch real-time weather information for any location using the wttr.in API.

Provides comprehensive access to Open-Meteo APIs for weather forecasts, historical data, air quality, and marine conditions. It enables LLMs to query specialized meteorological models, perform geocoding, and access advanced climate or flood projections.

Provides a Model Context Protocol server that enables large language models to query and retrieve real-time weather forecasts for cities and regions across China.

A comprehensive template for building MCP servers with TypeScript, Fastify, and Docker support. Includes tools for calculations and weather data, resources for server information, and prompts for greetings with full development tooling.

A demonstration project for Model Context Protocol (MCP) that integrates weather services with multiple AI models (Claude, GPT, Gemini), enabling natural language queries for weather alerts and forecasts.

A customizable Model Context Protocol server implementation that enables AI models to interact with external tools including weather queries, Google search, and camera control functionality.

Enables querying NASA POWER historical solar, wind, building, and agroclimatology data via MCP, including point time series, climatologies, native-grid regions, and comparisons across multiple labeled locations, with staged SQL analysis for larger datasets. Runs over STDIO or Streamable HTTP and requires no NASA account or API key.

An MCP server that offers arithmetic operations (addition and division) and current weather data from OpenWeatherMap. It serves as a learning project for building MCP servers with Node.js and TypeScript, supporting both stdio and Streamable HTTP transports.

A Model Context Protocol server that enables AI models to fetch weather alerts and detailed forecasts for US locations using the National Weather Service API.

An MCP server that aggregates data from six weather sources to provide current conditions, forecasts, air quality, and aviation METAR information, specifically optimized for European and Nordic locations. It supports multi-source data merging and functions without API keys for several integrated providers.

Enables retrieval of weather information for major cities across Japan using the Japan Meteorological Agency API. Supports weather overviews, precipitation probability, and wind speed data with both local and remote OAuth 2.0 authenticated deployment options.

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.

EU Crop Intelligence MCP Server — Yield forecasts, weather analysis, and phenology models for 15 countries. AI agent-native, multi-source intelligence (NASA POWER, Eurostat, Open-Meteo).

Enables any MCP-compatible assistant to plan sailing passages using wind and sea forecasts, with boat-specific polars, per-leg ETAs, complexity scores, and deep links to interactive plans. Works globally, with higher-resolution models over France, and supports multi-day departure window comparisons.

Provides real-time weather information for any location using the Open-Meteo API, enabling AI models to query current weather data through the Model Context Protocol.

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.