cognee is an open-source memory layer for AI agents. It ingests data from warehouses, vector stores, files, and APIs, then automatically builds a managed world model with ontologies, permissions, and recall tuning. Agents can retrieve relevant context across sessions, with memory that improves through use. It integrates with agent runtimes like Claude Code, LangGraph, CrewAI, and any MCP-compatible system.
Key Features
- Ingest from multiple sources: Connect Snowflake, Postgres, PDFs, Markdown, REST APIs, Slack, and more.
- Auto-extracted ontologies: Cognee builds and manages a world model from your data.
- Permissions and recall tuning: Fine-grained access control and memory that compounds with each run.
- Drop-in integration: Works with Claude Code, Codex, Cursor, LangGraph, CrewAI, Continue, Hermes, OpenClaw, and MCP.
Use Cases
- Research memory: Bayer compressed 10,000 scientific papers into agentic research memory.
- Evidence-based answers: University of Wyoming turned scattered K-5 research into cited, page-linked answers.
- Student community mapping: Knowunity connected 40,000 isolated learners using cognee.
Who It’s For
- Solo developers and agent hackers
- Data and platform teams
- Product engineers and founders shipping vertical agents
Key Benefits
- Open-source and free for local development
- Integrates with popular agent runtimes like Claude Code and MCP
- Automatically builds and improves memory from usage
- Supports multiple data sources and formats