Provides a persistent hierarchical task tree for LLM agents, enabling them to decompose work, track progress, record results, and handle failures outside the context window, with an optional web UI for monitoring and control.
A multi-agent task management system for AI applications that enables users to create agents with roles and capabilities, delegate tasks with trust-based routing, coordinate file access to prevent conflicts, and monitor performance through a unified dashboard.
An AI agent task management system that provides structure and visualization for long-term task planning with support for the Model Context Protocol (MCP) standard.
A minimal task management system for LLM agent collaboration via the Model Context Protocol, supporting CRUD operations, task blocking, subtasks, queues, and comments.
