ATLAS: Task Management System MCP Server

What is ATLAS: Task Management System?

ATLAS (Adaptive Task & Logic Automation System) is a project, knowledge, and task management system for LLM agents, built on a 3-node architecture of Projects, Tasks, and Knowledge. It uses Neo4j as its graph database and communicates via the Model Context Protocol (MCP), enabling standardized interaction between AI models and external systems.

How to use ATLAS: Task Management System?

Clone the repository, install dependencies (npm install), configure a Neo4j instance (self-hosted via Docker or cloud via Neo4j AuraDB), build the project (npm run build), and run the server using npm run start:stdio (default) or npm run start:http. Environment variables such as NEO4J_URI, NEO4J_USER, and NEO4J_PASSWORD must be set in your MCP client config or a .env file.

Key features of ATLAS: Task Management System

• Project management with metadata, statuses, and bulk operations
• Task lifecycle management with prioritization and categorization
• Knowledge repository with domain categorization and citation support
• Native dependency tracking for projects and tasks
• Cross-entity search with fuzzy matching and wildcard support
• Multiple transport modes: stdio and Streamable HTTP

Use cases of ATLAS: Task Management System

• LLM agents tracking and updating project progress autonomously
• Managing complex task workflows with prerequisite dependencies
• Building and querying a structured knowledge base for project teams
• Unified search across projects, tasks, and knowledge items
• Integrating task management into IDEs or chat-based assistants via MCP