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.
Server-enforced workflow discipline for AI agents. An MCP server providing persistent work items, dependency graphs, quality gates, and actor attribution. Schemas define what agents must produce — the server blocks the call if they don't. Works with any MCP-compatible client.
MCP server that orchestrates multi-agent reviews by running installed agent CLIs, tracking child tasks, and using Compare to produce a traceable recommended answer with receipts.
Evidence-first delivery audit MCP server that evaluates task requirements against delivery evidence and returns a reproducible pass/needs_review/fail decision with a deterministic receipt.
MCP server that provides a live coordination layer for AI agents, including attributable handoffs, a shared event ledger, atomic work-claiming, and advisory file leases to prevent collisions.
