ATLAS: Task Management System

ATLAS (Adaptive Task & Logic Automation System) is a task management system for LLM Agents.

Built on a three-tier architecture:

Implemented as a Model Context Protocol (MCP) server, ATLAS allows LLM agents to interact with project management database, enabling managing projects, tasks, and knowledge items.

Important Version Note: Version 1.5.4 is the last version that uses SQLite as the database. Version 2.0 and onwards has been completely rewritten to use Neo4j, which requires either:

• Self-hosting using Docker (docker-compose included in repository)
• Using Neo4j AuraDB cloud service: https://neo4j.com/product/auradb/

Version 2.5.0 introduces a new 3-node system (Projects, Tasks, Knowledge) that replaces the previous structure.

Table of Contents

• Overview
• Features
• Installation
• Configuration
• Project Structure
• Tools
• Resources
• Database Backup and Restore
• Examples
• Contributing
• License

Overview

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

• Clients: Claude Desktop, IDEs, and other MCP-compatible clients
• Servers: Tools and resources for project, task, and knowledge management
• LLM Agents: AI models that leverage the server's management capabilities

System Integration

The Atlas Platform integrates these components into a cohesive system:

• Project-Task Relationship: Projects contain tasks that represent actionable steps needed to achieve project goals. Tasks inherit context from their parent project while providing granular tracking of individual work items.
• Knowledge Integration: Both projects and tasks can be enriched with knowledge items, providing team members with necessary information and context.
• Dependency Management: Both projects and tasks support dependency relationships, allowing for complex workflows with prerequisites and sequential execution requirements.
• Unified Search: The platform provides cross-entity search capabilities, allowing users to find relevant projects, tasks, or knowledge based on various criteria.

Features

Project Management

• Comprehensive Tracking: Manage project metadata, statuses, and rich content (notes, links, etc.) with built-in support for bulk operations.
• Dependency & Relationship Handling: Automatically validate and track inter-project dependencies.

Task Management

• Task Lifecycle Management: Create, track, and update tasks through their entire lifecycle.
• Prioritization & Categorization: Assign priority levels and categorize tasks with tags for better organization.
• Dependency Tracking: Establish task dependencies to create structured workflows.

Knowledge Management

• Structured Knowledge Repository: Maintain a searchable repository of project-related information.
• Domain Categorization: Organize knowledge by domain and tags for easy retrieval.
• Citation Support: Track sources and references for knowledge items.

Graph Database Integration

• Native Relationship Management: Leverage Neo4j's ACID-compliant transactions and optimized queries for robust data integrity.
• Advanced Search & Scalability: Perform property-based searches with fuzzy matching and wildcards while maintaining high performance.

Unified Search

• Cross-Entity Search: Find relevant projects, tasks, or knowledge based on content, metadata, or relationships.
• Flexible Query Options: Support for case-insensitive, fuzzy, and advanced filtering options.

Installation

1. Clone the repository:

2. Install dependencies:

3. Configure Neo4j:

4. Build the project:

Configuration

Environment Variables

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

MCP Client Settings

Add to your MCP client settings:

Project Structure

The codebase follows a modular structure:

Tools

ATLAS provides a comprehensive suite of tools for project, task, and knowledge management, callable via the Model Context Protocol.

Project Operations

atlas_project_create

Creates new projects (single or bulk).

• Key Arguments: mode ('single'/'bulk'), project details (name, description, status, urls, completionRequirements, dependencies, outputFormat, taskType). Bulk mode uses a projects array.

atlas_project_list

Lists projects (all or details for one).

• Key Arguments: mode ('all'/'details'), id (for details), filters (status, taskType), pagination (page, limit), includes (includeKnowledge, includeTasks).

atlas_project_update

Updates existing projects (single or bulk).

• Key Arguments: mode ('single'/'bulk'), id, updates object (containing fields to change). Bulk mode uses a projects array with id and updates.

atlas_project_delete

Deletes projects (single or bulk).

• Key Arguments: mode ('single'/'bulk'), id (for single) or projectIds array (for bulk).

Task Operations

atlas_task_create

Creates new tasks (single or bulk) associated with a project.

• Key Arguments: mode ('single'/'bulk'), projectId, task details (title, description, priority, status, assignedTo, tags, completionRequirements, dependencies, outputFormat, taskType). Bulk mode uses a tasks array.

atlas_task_update

Updates existing tasks (single or bulk).

• Key Arguments: mode ('single'/'bulk'), id, updates object (containing fields to change). Bulk mode uses a tasks array with id and updates.

atlas_task_delete

Deletes tasks (single or bulk).

• Key Arguments: mode ('single'/'bulk'), id (for single) or taskIds array (for bulk).

atlas_task_list

Lists tasks for a specific project.

• Key Arguments: projectId (required), filters (status, assignedTo, priority, tags, taskType), sorting (sortBy, sortDirection), pagination (page, limit).

Knowledge Operations

atlas_knowledge_add

Adds new knowledge items (single or bulk) associated with a project.

• Key Arguments: mode ('single'/'bulk'), projectId, knowledge details (text, tags, domain, citations). Bulk mode uses a knowledge array.

atlas_knowledge_delete

Deletes knowledge items (single or bulk).

• Key Arguments: mode ('single'/'bulk'), id (for single) or knowledgeIds array (for bulk).

atlas_knowledge_list

Lists knowledge items for a specific project.

• Key Arguments: projectId (required), filters (tags, domain, search), pagination (page, limit).

Search Operations

atlas_unified_search

Performs a unified search across projects, tasks, and knowledge.

• Key Arguments: value (search term), property (optional field to search), filters (entityTypes, taskType), options (caseInsensitive, fuzzy), pagination (page, limit).

Database Operations

atlas_database_clean

Destructive: Completely resets the database, removing all projects, tasks, and knowledge.

• Key Arguments: acknowledgement (must be set to true to confirm).

Resources

ATLAS exposes project, task, and knowledge data through standard MCP resource endpoints.

Direct Resources

atlas://projects

• Description: List of all projects in the Atlas platform with pagination support.

atlas://tasks

• Description: List of all tasks in the Atlas platform with pagination and filtering support.

atlas://knowledge

• Description: List of all knowledge items in the Atlas platform with pagination and filtering support.

Resource Templates

atlas://projects/{projectId}

• Description: Retrieves a single project by its unique identifier (projectId).

atlas://tasks/{taskId}

• Description: Retrieves a single task by its unique identifier (taskId).

atlas://projects/{projectId}/tasks

• Description: Retrieves all tasks belonging to a specific project (projectId).

atlas://knowledge/{knowledgeId}

• Description: Retrieves a single knowledge item by its unique identifier (knowledgeId).

atlas://projects/{projectId}/knowledge

• Description: Retrieves all knowledge items belonging to a specific project (projectId).

Database Backup and Restore

ATLAS provides functionality to back up and restore the Neo4j database content. The core logic resides in src/services/neo4j/backupRestoreService.ts.

Automatic Backups (Note)

Important: The automatic backup functionality is currently not working. Please use the manual backup process described below until this feature is fully implemented.

The src/services/neo4j/driver.ts includes a triggerBackgroundBackup function that is intended to call exportDatabase after every write operation, but this feature is still under development. For now, rely on regular manual backups to protect your data.

Backup Process

• Mechanism: The backup process exports all Project, Task, and Knowledge nodes, along with their relationships, into separate JSON files.
• Output: Each backup creates a timestamped directory (e.g., atlas-backup-YYYYMMDDHHMMSS) within the configured backup path (default: ./atlas-backups/). This directory contains projects.json, tasks.json, knowledge.json, and relationships.json.
• Manual Backup: You can trigger a manual backup using the provided script:
  npm run db:backup
  This command executes scripts/db-backup.ts, which calls the exportDatabase function.

Restore Process

• Mechanism: The restore process first completely clears the existing Neo4j database. Then, it imports nodes and relationships from the JSON files located in the specified backup directory.
• Warning: Restoring from a backup is a destructive operation. It will overwrite all current data in your Neo4j database.
• Manual Restore: To restore the database from a backup directory, use the import script:
  npm run db:import <path_to_backup_directory>
  Replace <path_to_backup_directory> with the actual path to the backup folder (e.g., ./atlas-backups/atlas-backup-20250326120000). This command executes scripts/db-import.ts, which calls the importDatabase function.
• Relationship Handling: The import process attempts to recreate relationships based on the id properties stored within the nodes during export. Ensure your nodes have consistent id properties for relationships to be restored correctly.

Examples

The examples/ directory contains practical examples demonstrating various features of the ATLAS MCP Server.

• Backup Example: Located in examples/backup-example/, this shows the structure and format of the JSON files generated by the npm run db:backup command. See the Examples README for more details.

Contributing

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

For bugs and feature requests, please create an issue.

License

Apache License 2.0