Most task tools give you a flat list; here projects and tasks can depend on each other, knowledge attaches to a project, and one query crosses all three. atlas_deep_research is the clearest use of that: a topic goes in and comes back as a plan of linked sub-questions with tasks attached, not a document.
A project, task and knowledge manager backed by Neo4j, exposed as MCP tools. Entities carry dependencies and relationships, and one search spans all three.
- atlas_project_create, atlas_project_list, atlas_project_update and atlas_project_delete — projects with status, URLs, completion requirements and dependencies, single or bulk
- atlas_task_create, atlas_task_update, atlas_task_delete and atlas_task_list — tasks with priority, tags, assignee and dependencies, listed per project
- atlas_knowledge_add, atlas_knowledge_list and atlas_knowledge_delete — knowledge items with domain, tags and citations
- atlas_unified_search — one search across projects, tasks and knowledge, full-text or regex, with case-insensitive and fuzzy options
- atlas_deep_research — turns a topic and goal into a hierarchical research plan in the graph, optionally creating tasks for each sub-question
- Resource endpoints under atlas:// for projects, tasks and knowledge, including per-project listings
- Backup and restore to timestamped JSON exports
A reachable Neo4j instance — the repository ships a docker-compose for one — with NEO4J_URI, NEO4J_USER and NEO4J_PASSWORD set. Node and npm to install and build. Runs over stdio by default, or as Streamable HTTP with MCP_TRANSPORT_TYPE set to http.
One command plus a key — npx -y atlas-mcp-server, then supply credentials