cognee

cognee is a vector database - Cognee is the open-source AI memory platform for agents. Give your AI agents persistent long-term memory across sessions with a self-hosted knowledge graph engine.

Overview

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Cognee is the open-source AI memory platform that gives AI agents persistent long-term memory across sessions. Ingest data in any format, build a self-hosted knowledge graph, and let every agent recall, connect, and act with full context

📄 Read the research paper: Optimizing the Interface Between Knowledge Graphs and LLMs for Complex Reasoning — Markovic et al., 2025

Cognee is an open-source AI memory platform for AI Agents. Ingest data in any format, and Cognee continuously builds a self-hosted knowledge graph that gives your agents persistent long-term memory across sessions. Cognee combines vector embeddings, graph reasoning, and cognitive-science-grounded ontology generation to make documents both searchable by meaning and connected by relationships that evolve as your knowledge does.

:star: Help us reach more developers and grow the cognee community. Star this repo!

:books: Check our detailed documentation for setup and configuration.

To learn more, check out this short, end-to-end Colab walkthrough of Cognee's core features.

You can install Cognee with pip, poetry, uv, or your preferred Python package manager.

To integrate other LLM providers, see our LLM Provider Documentation.

cognee is open-source, written primarily in Python, with 17,717 GitHub stars under the Apache 2.0 license. The latest release is v1.1.2 (2026-05-30).

Key capabilities

From the project's documentation:

• Easily Build Company Brain - unify data from various sources in one place and enable Agents with your domain knowledge
• Knowledge infrastructure — unified ingestion, graph/vector search, runs locally, ontology grounding, multimodal
• Persistent and Learning Agents - learn from feedback, context management, cross-agent knowledge sharing
• Reliable and Trustworthy Agents - agentic user/tenant isolation, traceability, OTEL collector, audit traits
• Python 3.10 to 3.14

Install

A quick way to get started (always check the official docs for the latest):

pip install cognee

How it fits a local-AI stack

cognee runs on your own hardware, so pair it with a model and a GPU sized to your needs. Use the VRAM calculator to pick a model that fits your card, and see what you can run for hardware guidance. Related vector databases in the directory:

• Chroma
• Milvus
• Qdrant
• Weaviate

Sources

• Source code & docs: topoteretes/cognee
• Official website: https://www.cognee.ai

Stats from GitHub, 2026-06-08.