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.
A task-based AI orchestrator that bridges AI models (Gemini, Claude, OpenAI) with local environments, operating as an interactive CLI and an MCP server for structured autonomous development.
An MCP-native agentic platform orchestrating planner/executor/critic agents over hybrid RAG with three-tier memory, budget enforcement, safety guardrails, and full observability. It exposes all capabilities as MCP tools, enabling natural-language control of document ingestion, retrieval-augmented generation, and multi-step AI workflows.
The coordination layer for AI agent networks, providing persistent memory, task management, inter-agent messaging, and human oversight through native MCP tools.
Unified MCP orchestration layer that consolidates multiple MCPs into a single interface with semantic tool discovery, code-mode execution, scheduling, and intelligent caching to reduce token usage by 97% and eliminate choice paralysis.
A local-first mission control for AI agent harnesses, providing a unified MCP gateway for shared memory, task queue, and encrypted secrets across multiple agents.
