📌Overview

Purpose: ATLAS aims to streamline task management for LLM agents by providing an efficient system for organizing and automating project tasks and knowledge.

Overview: ATLAS is built on the Model Context Protocol (MCP) to facilitate seamless interaction between LLMs and project management tasks. It adopts a three-tier architecture that organizes details into Projects, Tasks, and Knowledge components, allowing for comprehensive management of project workflows and dependencies.

Key Features:

• Project Management: Provides tools for tracking project metadata, handling dependencies, and managing project statuses and content through bulk operations.

• Task Management: Enables the creation, tracking, and updating of tasks with lifecycle management, prioritization, categorization, and dependency tracking to ensure structured workflows.

• Knowledge Management: Features a searchable repository for project-related information, organized by domain and tags, supporting citation tracking for knowledge items.

• Graph Database Integration: Utilizes Neo4j for robust data integrity, advanced search capabilities, and optimized query performance, ensuring scalability and efficient management of relationships.

• Unified Search: Offers cross-entity search across projects, tasks, and knowledge for easily retrieving relevant information based on various criteria and filtering options.

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ATLAS: Task Management System

ATLAS (Adaptive Task & Logic Automation System) is a task management system for LLM Agents, built on a three-tier architecture: Projects, Tasks, and Knowledge.

Overview

ATLAS implements the Model Context Protocol (MCP), enabling standardized communication between LLMs and external systems, including:

• Clients: Various MCP-compatible clients.
• Servers: Tools for project, task, and knowledge management.
• LLM Agents: AI models leveraging the server's capabilities.

System Integration

• Project-Task Relationship: Tasks within projects inherit context for better tracking.
• Knowledge Integration: Enriching projects and tasks with knowledge items.
• Dependency Management: Supporting dependencies for complex workflows.
• Unified Search: Cross-entity search capabilities across projects, tasks, and knowledge.

Features

Project Management

• Comprehensive tracking of project metadata and statuses.
• Automatic dependency validation.

Task Management

• Lifecycle management for tasks.
• Prioritization and categorization through tags.
• Dependency tracking for structured workflows.

Knowledge Management

• A searchable repository of project-related information.
• Organization by domain and tags for easy retrieval.

Graph Database Integration

• Native relationship management using Neo4j for data integrity.
• High-performance property-based searches.

Installation

1. Clone the repository:

   git clone https://github.com/cyanheads/atlas-mcp-server.git
   cd atlas-mcp-server
   

2. Install dependencies:

   npm install
   

3. Configure Neo4j:

   docker-compose up -d
   

4. Build the project:

   npm run build
   

Configuration

Create a .env file based on .env.example:

NEO4J_URI=bolt://localhost:7687
NEO4J_USER=neo4j
NEO4J_PASSWORD=password2

LOG_LEVEL=info
NODE_ENV=development

Project Structure

The codebase follows a modular structure:

src/
├── config/
├── index.ts
├── mcp/
├── services/
├── types/
└── utils/

Tools

ATLAS provides tools callable via the Model Context Protocol for:

• Project Operations: Create, list, update, delete projects.
• Task Operations: Create, update, delete, list tasks.
• Knowledge Operations: Add, delete, list knowledge items.
• Search Operations: Perform unified searches across entities.

Database Backup and Restore

ATLAS supports backup and restore functionality for the Neo4j database.

Backup Process

• Exports all Project, Task, and Knowledge nodes along with relationships into separate JSON files.
• Trigger manual backup:

  npm run db:backup
  

Restore Process

• Clears existing Neo4j database before importing nodes and relationships from JSON files.
• Restore command:

  npm run db:import <path_to_backup_directory>
  

Examples

Practical examples demonstrating various ATLAS features can be found in the examples/ directory.

Contributing

1. Fork the repository.
2. Create a feature branch.
3. Commit changes with a descriptive message.
4. Push to the branch.
5. Create a Pull Request.

License

Apache License 2.0