An MCP server that routes LLM requests across multiple providers and orchestrates other MCP servers, with a focus on local privacy for embeddings and memory.
MCP server that enables AI agents to run a deterministic orchestration loop with decomposition, subagent execution, and review feedback across multiple LLM backends.
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.
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 open-source MCP server that enables secure AI-to-AI collaboration across organizations without sharing system prompts, private data, model weights, or internal memory.