An MCP server that enables human-in-the-loop elicitation, letting AI agents ask users questions via tools like elicit_confirm and elicit_form, with diagnostics to verify host elicitation support.
A demonstration server that showcases how to collect user input dynamically using the Model Context Protocol (MCP) elicitation system across tools, resources, and prompts.
A testing server for MCP client implementations that provides tools for echoing data, error handling, timing operations, data generation, LLM sampling, and user elicitations.
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.