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 testing environment for Model Context Protocol that enables exploration of MCP capabilities and integration of AI models with external data sources and tools.
A comprehensive reference implementation demonstrating all features of the Model Context Protocol (MCP) specification, serving as documentation, learning resource, and testing tool for MCP implementations.
A production-grade MCP server that provides real-time weather data and demonstrates the complete MCP protocol surface including tools, resources, prompts, and structured output.
A basic Model Context Protocol server implementation that demonstrates core MCP functionality including tools and resources. Provides weather alerts through the Weather API and serves as a learning example for MCP development.
Hosted MCP server for weather forecast data. Enables AI agents to discover datasets, build validated API requests, and execute live weather queries after OAuth.