An MCP server that lets agents and humans monitor and control long-running processes, reducing copy-pasting between AI tools and enabling multiple agents to interact with the same process outputs.
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 that provides AI agents with persistent memory, cross-agent sharing, and context management, enabling them to remember conversations, track complex tasks, and evolve skills across tools.
An MCP server that exposes deterministic workflows as tools, allowing small models to reliably orchestrate APIs and other MCP servers with minimal parameters.