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atlas-mcp-server

by cyanheads
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TypeScript
Apache 2.0
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ATLAS: Task Management System

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

Built on a three-tier architecture:

+------------------------------------------+ | PROJECT | |------------------------------------------| | id: string | | name: string | | description: string | | status: string | | urls?: Array<{title: string, url: string}>| | completionRequirements: string | | outputFormat: string | | taskType: string | | createdAt: string | | updatedAt: string | +----------------+-------------------------+ | | | | v v +----------------------------------+ +----------------------------------+ | TASK | | KNOWLEDGE | |----------------------------------| |----------------------------------| | id: string | | id: string | | projectId: string | | projectId: string | | title: string | | text: string | | description: string | | tags?: string[] | | priority: string | | domain: string | | status: string | | citations?: string[] | | assignedTo?: string | | createdAt: string | | urls?: Array<{title: string, | | | | url: string}> | | updatedAt: string | | tags?: string[] | | | | completionRequirements: string | | | | outputFormat: string | | | | taskType: string | | | | createdAt: string | | | | updatedAt: string | | | +----------------------------------+ +----------------------------------+

Implemented as a Model Context Protocol (MCP) server, ATLAS allows LLM agents to interact with a project management database, enabling them to manage 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:

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

Table of Contents

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.
  • 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:
    git clone https://github.com/cyanheads/atlas-mcp-server.git cd atlas-mcp-server
  2. Install dependencies:
    npm install
  3. Configure Neo4j: Ensure you have a Neo4j instance running and accessible. You can start one using the provided Docker configuration:
    docker-compose up -d
    Update your .env file with the Neo4j connection details (see Configuration).
  4. Build the project:
    npm run build

Running the Server

Most MCP Clients run the server automatically, but you can also run it manually for testing or development purposes using the following commands.

ATLAS MCP Server supports multiple transport mechanisms for communication:

  • Standard I/O (stdio): This is the default mode and is typically used for direct integration with local MCP clients (like IDE extensions).
    npm run start:stdio
    This uses the MCP_TRANSPORT_TYPE=stdio setting.
  • Streamable HTTP: This mode allows the server to listen for MCP requests over HTTP, suitable for remote clients or web-based integrations.
    npm run start:http
    This uses the MCP_TRANSPORT_TYPE=http setting. The server will listen on the host and port defined in your .env file (e.g., MCP_HTTP_HOST and MCP_HTTP_PORT, defaulting to 127.0.0.1:3010). Ensure your firewall allows connections if accessing remotely.

Web UI (Experimental)

A basic Web UI is available for viewing Project, Task, & Knowledge details.

  • Opening the UI:
    • To open the UI directly in your browser, run the following command in your terminal:
      npm run webui
  • Functionality:
    • You can see an example screenshot of the Web UI here.

Configuration

Environment Variables

Environment variables should be set in the client config in your MCP Client, or in a .env file in the project root for local development.

# Neo4j Configuration NEO4J_URI=bolt://localhost:7687 NEO4J_USER=neo4j NEO4J_PASSWORD=password2 # Application Configuration MCP_LOG_LEVEL=debug # Minimum logging level. Options: emerg, alert, crit, error, warning, notice, info, debug. Default: "debug". LOGS_DIR=./logs # Directory for log files. Default: "./logs" in project root. NODE_ENV=development # 'development' or 'production'. Default: "development". # MCP Transport Configuration MCP_TRANSPORT_TYPE=stdio # 'stdio' or 'http'. Default: "stdio". MCP_HTTP_HOST=127.0.0.1 # Host for HTTP transport. Default: "127.0.0.1". MCP_HTTP_PORT=3010 # Port for HTTP transport. Default: 3010. # MCP_ALLOWED_ORIGINS=http://localhost:someport,https://your-client.com # Optional: Comma-separated list of allowed origins for HTTP CORS. # MCP Security Configuration # MCP_AUTH_SECRET_KEY=your_very_long_and_secure_secret_key_min_32_chars # Optional: Secret key (min 32 chars) for JWT authentication if HTTP transport is used. CRITICAL for production. *Note: Production environment use has not been tested yet.* MCP_RATE_LIMIT_WINDOW_MS=60000 # Rate limit window in milliseconds. Default: 60000 (1 minute). MCP_RATE_LIMIT_MAX_REQUESTS=100 # Max requests per window per IP for HTTP transport. Default: 100. # Database Backup Configuration BACKUP_MAX_COUNT=10 # Maximum number of backup sets to keep. Default: 10. BACKUP_FILE_DIR=./atlas-backups # Directory where backup files will be stored (relative to project root). Default: "./atlas-backups". # OpenRouter LLM Configuration (Optional - additional parameters present in `src/config/index.ts`) # OPENROUTER_API_KEY=your_openrouter_api_key # API key for OpenRouter services. LLM_DEFAULT_MODEL="google/gemini-2.5-flash-preview:thinking" # Default LLM model.

Refer to src/config/index.ts for all available environment variables, their descriptions, and default values.

MCP Client Settings

How you configure your MCP client depends on the client itself and the chosen transport type. An mcp.json file in the project root can be used by some clients (like mcp-inspector) to define server configurations; update as needed.

For Stdio Transport (Example Configuration):

{ "mcpServers": { "atlas-mcp-server-stdio": { "command": "node", "args": ["/full/path/to/atlas-mcp-server/dist/index.js"], "env": { "NEO4J_URI": "bolt://localhost:7687", "NEO4J_USER": "neo4j", "NEO4J_PASSWORD": "password2", "MCP_LOG_LEVEL": "info", "NODE_ENV": "production", "MCP_TRANSPORT_TYPE": "stdio" } } } }

For Streamable HTTP (Example Configuration): If your client supports connecting to an MCP server via Streamable HTTP, you provide the server's endpoint (e.g., http://localhost:3010/mcp) in your client configuration.

{ "mcpServers": { "atlas-mcp-server-http": { "command": "node", "args": ["/full/path/to/atlas-mcp-server/dist/index.js"], "env": { "NEO4J_URI": "bolt://localhost:7687", "NEO4J_USER": "neo4j", "NEO4J_PASSWORD": "password2", "MCP_LOG_LEVEL": "info", "NODE_ENV": "production", "MCP_TRANSPORT_TYPE": "http", "MCP_HTTP_PORT": "3010", "MCP_HTTP_HOST": "127.0.0.1" // "MCP_AUTH_SECRET_KEY": "your-secure-token" // If authentication is enabled on the server } } } }

Note: Always use absolute paths for args when configuring client commands if the server is not in the client's immediate working directory. The MCP_AUTH_SECRET_KEY in the client's env block is illustrative; actual token handling for client-to-server communication would depend on the client's capabilities and the server's authentication mechanism (e.g., sending a JWT in an Authorization header).

Project Structure

The codebase follows a modular structure:

src/ ├── config/ # Configuration management (index.ts) ├── index.ts # Main server entry point ├── mcp/ # MCP server implementation (server.ts) │ ├── resources/ # MCP resource handlers (index.ts, types.ts, knowledge/, projects/, tasks/) │ └── tools/ # MCP tool handlers (individual tool directories) ├── services/ # Core application services │ ├── llm-providers/ # LLM provider integrations (e.g., OpenRouter) │ └── neo4j/ # Neo4j database services (index.ts, driver.ts, backupRestoreService.ts, etc.) ├── types/ # Shared TypeScript type definitions (errors.ts, mcp.ts, tool.ts) └── utils/ # Utility functions and internal services (e.g., logger, errorHandler, sanitization)

Tools

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

Project Operations

Tool NameDescriptionKey Arguments
atlas_project_createCreates new projects (single/bulk).mode ('single'/'bulk'), id (optional client-generated ID for single mode), project details (name, description, status, urls, completionRequirements, dependencies, outputFormat, taskType). For bulk mode, use projects (array of project objects). responseFormat ('formatted'/'json', optional, default: 'formatted').
atlas_project_listLists projects (all/details).mode ('all'/'details', default: 'all'), id (for details mode), filters (status, taskType), pagination (page, limit), includes (includeKnowledge, includeTasks), responseFormat ('formatted'/'json', optional, default: 'formatted').
atlas_project_updateUpdates existing projects (single/bulk).mode ('single'/'bulk'), id (for single mode), updates object. For bulk mode, use projects (array of objects, each with id and updates). responseFormat ('formatted'/'json', optional, default: 'formatted').
atlas_project_deleteDeletes projects (single/bulk).mode ('single'/'bulk'), id (for single mode) or projectIds (array for bulk mode). responseFormat ('formatted'/'json', optional, default: 'formatted').

Task Operations

Tool NameDescriptionKey Arguments
atlas_task_createCreates new tasks (single/bulk).mode ('single'/'bulk'), id (optional client-generated ID), projectId, task details (title, description, priority, status, assignedTo, urls, tags, completionRequirements, dependencies, outputFormat, taskType). For bulk mode, use tasks (array of task objects). responseFormat ('formatted'/'json', optional, default: 'formatted').
atlas_task_updateUpdates existing tasks (single/bulk).mode ('single'/'bulk'), id (for single mode), updates object. For bulk mode, use tasks (array of objects, each with id and updates). responseFormat ('formatted'/'json', optional, default: 'formatted').
atlas_task_deleteDeletes tasks (single/bulk).mode ('single'/'bulk'), id (for single mode) or taskIds (array for bulk mode). responseFormat ('formatted'/'json', optional, default: 'formatted').
atlas_task_listLists tasks for a specific project.projectId (required), filters (status, assignedTo, priority, tags, taskType), sorting (sortBy, sortDirection), pagination (page, limit), responseFormat ('formatted'/'json', optional, default: 'formatted').

Knowledge Operations

Tool NameDescriptionKey Arguments
atlas_knowledge_addAdds new knowledge items (single/bulk).mode ('single'/'bulk'), id (optional client-generated ID), projectId, knowledge details (text, tags, domain, citations). For bulk mode, use knowledge (array of knowledge objects). responseFormat ('formatted'/'json', optional, default: 'formatted').
atlas_knowledge_deleteDeletes knowledge items (single/bulk).mode ('single'/'bulk'), id (for single mode) or knowledgeIds (array for bulk mode). responseFormat ('formatted'/'json', optional, default: 'formatted').
atlas_knowledge_listLists knowledge items for a specific project.projectId (required), filters (tags, domain, search), pagination (page, limit), responseFormat ('formatted'/'json', optional, default: 'formatted').

Search Operations

Tool NameDescriptionKey Arguments
atlas_unified_searchPerforms unified search across entities.value (search term, required), property (optional: if specified, performs regex search on this property; if omitted, performs full-text search), filters (entityTypes, taskType, assignedToUserId), options (caseInsensitive (default: true, for regex), fuzzy (default: false, for regex 'contains' or full-text Lucene fuzzy)), pagination (page, limit), responseFormat ('formatted'/'json', optional, default: 'formatted').

Research Operations

Tool NameDescriptionKey Arguments
atlas_deep_researchInitiates a structured deep research process by creating a hierarchical plan within the Atlas knowledge base.projectId (required), researchTopic (required), researchGoal (required), scopeDefinition (optional), subTopics (required array of objects, each with question (required), initialSearchQueries (optional array), nodeId (optional), priority (optional), assignedTo (optional), initialStatus (optional, default: 'todo')), researchDomain (optional), initialTags (optional), planNodeId (optional), createTasks (optional, default: true), responseFormat ('formatted'/'json', optional, default: 'formatted').

Database Operations

Tool NameDescriptionKey Arguments
atlas_database_cleanDestructive: Completely resets the database, removing all projects, tasks, and knowledge.acknowledgement (must be set to true to confirm, required), responseFormat ('formatted'/'json', optional, default: 'formatted').

Resources

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

Direct Resources

Resource NameDescription
atlas://projectsList of all projects in the Atlas platform with pagination support.
atlas://tasksList of all tasks in the Atlas platform with pagination and filtering support.
atlas://knowledgeList of all knowledge items in the Atlas platform with pagination and filtering support.

Resource Templates

Resource NameDescription
atlas://projects/{projectId}Retrieves a single project by its unique identifier (projectId).
atlas://tasks/{taskId}Retrieves a single task by its unique identifier (taskId).
atlas://projects/{projectId}/tasksRetrieves all tasks belonging to a specific project (projectId).
atlas://knowledge/{knowledgeId}Retrieves a single knowledge item by its unique identifier (knowledgeId).
atlas://projects/{projectId}/knowledgeRetrieves 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.

Backup Process

  • Mechanism: The backup process exports all Project, Task, and Knowledge nodes, along with their relationships, into separate JSON files. A full-export.json containing all data is also created.
  • 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, relationships.json, and full-export.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. It prioritizes full-export.json if available.
  • 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.
  • Deep Research Example: Located in examples/deep-research-example/, this demonstrates the output and structure generated by the atlas_deep_research tool. It includes a markdown file (covington_community_grant_research.md) summarizing the research plan and a JSON file (full-export.json) containing the raw data exported from the database after the research plan was created. See the Examples README for more details.

License

Apache License 2.0

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Tools

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ATLAS (Adaptive Task & Logic Automation System) is a Model Context Protocol server that provides hierarchical task management capabilities to Large Language Models. This tool provides LLMs with the structure and context needed to manage complex tasks and dependencies.

  1. Table of Contents
    1. Overview
      1. System Integration
    2. Features
      1. Project Management
      2. Task Management
      3. Knowledge Management
      4. Graph Database Integration
      5. Unified Search
    3. Installation
      1. Running the Server
        1. Web UI (Experimental)
          1. Configuration
            1. Environment Variables
            2. MCP Client Settings
          2. Project Structure
            1. Tools
              1. Project Operations
              2. Task Operations
              3. Knowledge Operations
              4. Search Operations
              5. Research Operations
              6. Database Operations
            2. Resources
              1. Direct Resources
              2. Resource Templates
            3. Database Backup and Restore
              1. Backup Process
              2. Restore Process
            4. Examples
              1. License

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