Provides MCP tools that give LLM agents a full QA engineer workflow: scanning projects, generating deterministic test suites, executing them across browser/API/mobile, diagnosing failures, and proposing fixes that require human approval.
MCP server exposing statistical regression testing for LLM agents as a "run" tool: p-value, effect size, and confidence interval on whether agent behavior actually changed.
Exposes a deterministic AI-slop scanner and RAG grounding grader as MCP Tools, Resource, and Prompt, enabling any MCP client to evaluate text quality and context faithfulness.
Enables LLM evaluation and observability by uploading documents, building test sets, running RAG pipelines, and automatically scoring answers for groundedness, hallucination risk, retrieval quality, latency, and cost, with tools exposed to MCP-compatible clients.