An MCP server that exposes RAG retrieval evaluation as agent tools, allowing agents to retrieve passages and measure retrieval quality across multiple strategies.
A local MCP server that packages LLM evaluation gates as reusable CI/CD primitives, enabling AI agents to run datasets against models, score responses, and enforce quality thresholds.
MCP server that provides tools for evaluating LLM agent reliability, including adversarial task generation, automated LLM-as-judge assessment, and confidence statistics.