MCP server that enables AI agents to run a deterministic orchestration loop with decomposition, subagent execution, and review feedback across multiple LLM backends.
Enables enterprise multi-agent decision workflows that expose 8+ MCP tools such as SQL query, web search, Python sandbox, RAG, file access, data cleaning, chart generation, and HTTP calls, orchestrated with LangGraph, streaming output, and human-in-the-loop approvals.
Provides 300+ MCP tools for orchestrating AI agents — including swarm coordination, self-learning memory, and task management — enabling MCP clients like Claude Code and Cursor to spawn, coordinate, and learn from specialist agents across sessions.
An MCP server that exposes deterministic workflows as tools, allowing small models to reliably orchestrate APIs and other MCP servers with minimal parameters.
An MCP server for domain-agnostic task orchestration, turning objectives into executed workflows with built-in validation, security, and multi-agent patterns.