A multi-agent orchestrator MCP server that enables LLM agents to collaborate on complex tasks by automating role assignment, inter-agent communication, and artifact integration. It provides tools for task decomposition, agent assignment, status tracking, code review, and result merging.
An MCP server that turns independent AI agents into a coordinated engineering team with shared task board, context, review loop, and enforced plan-implement-review-iterate workflow.
Harness-agnostic MCP server for orchestrating deterministic, resumable multi-agent workflows. It lets you start, watch, resume, and cancel agent runs from any MCP client, using agents from Codex, Claude, Cursor, or Kimi.
MCP server that enables agents to dynamically switch between multiple AI models (OpenAI, Anthropic, Google, etc.) with unified protocol-driven configuration and capability discovery.
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.
