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 deterministic workflows as tools, allowing small models to reliably orchestrate APIs and other MCP servers with minimal parameters.
Enables multi-agent communication workflows with consensus arbitration, peer messaging, and operator-mediated collaboration through authenticated MCP tools.
Enables multiple AI models to collaborate under a shared goal, architecture, plan, loops, sandbox, and acceptance criteria via a local-first MCP server.
Enables AI agents to share knowledge, coordinate tasks, and maintain persistent memory across distributed infrastructure with secure vaults and 130+ MCP tools.