MCP server that enables AI agents to run a deterministic orchestration loop with decomposition, subagent execution, and review feedback across multiple LLM backends.
MCP server for agentic task orchestration and management, enabling AI agents to create goals, plan tasks with acceptance criteria, track dependencies, request human input, and provide proof of completion.
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.
An MCP server that enables AI coding agents to coordinate by sharing environment snapshots and diffs, surfacing overlapping work, exchanging debug-session messages, handing off tasks, and enforcing policy preflight checks.