Multi-agent AI orchestrator that runs parallel coding agents in isolated sessions with self-improving intelligence, exposed via an MCP server for task execution and management.
A powerful orchestration layer for Model Context Protocol (MCP) servers that enables AI assistants to dynamically discover, inspect, and interact with multiple MCP servers through a unified interface.
MCP server that enables AI agents to run a deterministic orchestration loop with decomposition, subagent execution, and review feedback across multiple LLM backends.
Intelligent server management MCP server that enables agents to write TypeScript code to organize and manage multiple MCP servers with self-improving capabilities.
MCP server that enables agents to dynamically switch between multiple AI models (OpenAI, Anthropic, Google, etc.) with unified protocol-driven configuration and capability discovery.