Evaluates RAG outputs on faithfulness, answer relevancy, and context precision using an LLM-as-a-Judge backend. Exposes tools for running evaluations, scoring individual samples, and checking thresholds, enabling CI gating and on-demand assessment via MCP.
Audits MCP server configurations for security risks including capability inventory, SSRF, prompt injection, and drift detection. Works in read-only mode and can also be used as an MCP server to let AI agents audit their own attack surface.
Policy-as-code gate for AI-SDLC, providing MCP tools to review prompts, diff tool manifests, vet MCP servers, and run evaluation suites for LLM agent repos.
MCP server for AI compliance auditing. Scores agent outputs for hallucination liability under the EU AI Act, issues verifiable compliance stamps, and tracks audit history by agent.
