MCP server that provides tools for evaluating LLM agent reliability, including adversarial task generation, automated LLM-as-judge assessment, and confidence statistics.
A local-first LLM routing MCP server that keeps sensitive data on your own models, with fail-closed privacy and manager-worker delegation, exposing route and complete tools to any MCP client.
An MCP server that exposes tools for sub-agent style reasoning across multiple LLM providers, enabling delegation of prompts to various models and running critique loops, debates, red-teaming, and answer ranking.
Unified MCP server for querying multiple LLM providers (Gemini, OpenAI, Anthropic, etc.) with advanced routing, cost optimization, and fallback resilience.
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.