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atlas-mcp-server

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Basic Information

This repository provides ATLAS, an MCP (Model Context Protocol) server implemented in TypeScript that exposes a project, task, and knowledge management system for LLM agents. It is designed as a 3-node architecture where Projects, Tasks, and Knowledge are first-class entities and can be related and enriched with metadata, dependencies, tags and citations. The server implements MCP resources and tools so MCP-compatible clients and agent models (for example IDE extensions or desktop clients) can create, list, update, delete and search projects, tasks and knowledge items programmatically. The project is built to run against a Neo4j graph database (transitioned from SQLite in earlier versions) and includes Docker compose configuration, environment-driven configuration, build and start scripts and an experimental web UI for browsing stored data.

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App URL
https://github.com/cyanheads/atlas-mcp-server
Github Repository
https://github.com/cyanheads/atlas-mcp-server/blob/main/README.md

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App Details

Features
ATLAS offers a comprehensive set of MCP tools and resource endpoints for managing projects, tasks and knowledge. Key capabilities include project lifecycle handling, bulk operations, task creation and prioritization, dependency tracking, a structured knowledge repository with domain and citation support, and a unified cross-entity search with fuzzy and case-insensitive options. The server integrates natively with Neo4j for ACID transactions, relationship modeling and scalable property-based queries. Transport mechanisms supported include stdio and streamable HTTP for local and remote MCP clients. Built-in utilities include database backup and restore scripts that export/import JSON snapshots, example workflows, an experimental web UI, environment configuration patterns and detailed tool argument schemas for each operation.
Use Cases
For developers building agent-driven automation or integrating LLMs with external tooling, ATLAS provides a ready-made MCP server that exposes structured project and knowledge management primitives. Agents can programmatically orchestrate plans, create hierarchical research plans, manage task dependencies and update project state using standard MCP calls. Neo4j backing offers robust relationship management and performant search for context-aware agent reasoning. The included examples, backup/restore tools, docker-compose for Neo4j, and client configuration examples (mcp.json and env variables) reduce setup friction for self-hosting or connecting to cloud Neo4j services. Command scripts and transport options let teams test locally or integrate ATLAS into existing MCP-capable clients and development workflows.

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