A minimal demonstration server showcasing MCP protocol capabilities including tools, resources, and prompts with basic examples like hello world functionality.
A foundational implementation of a Model Context Protocol (MCP) server designed for educational purposes. It demonstrates the complete interaction between an LLM, an inference engine, and a client during an agentic call.
A minimal learning-focused MCP server that demonstrates core primitives like tools and resources through simple greeting functions. It provides a foundational example for connecting AI models to external data using both Streamable HTTP and stdio transports.
A demo MCP server that showcases the 2026-07-28 MCP protocol revision features: discover, stateless calls, multi-round-trip requests, subscriptions, and cache hints. It also maintains backward compatibility with legacy 2025-11-25 clients.
A minimal, well-structured MCP server implementation for learning and experimentation that exposes three tools: web search, API search, and client ID processing. It demonstrates clean separation between tool, transport, and LLM layers while supporting multiple AI clients through the Model Context Protocol standard.