MCP server that experiments with cheaper LLM policies (model, prompt, reasoning, retry, escalation) against project tasks to recommend the lowest-cost policy that meets quality constraints.
Enables policy-governed MCP interactions with deterministic authorization, tenant isolation, minimized PII exposure, and human approval gates for sensitive mutations, while producing structured audit events.
LLM routing proxy that cuts API costs 60-90% by auto-selecting the cheapest capable model across OpenAI, Anthropic, and Google. Provides stats, config, and model comparison tools via MCP.
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.