Agen & Multi-Agen

Cognee: Open-Source Persistent Memory for AI Agents

topoteretes/cognee

Cognee is a Python-based AI memory platform that turns ingested data into persistent, self-hosted knowledge graph memory. It combines vector embeddings, graph reasoning and ontology generation so agents can retrieve context across sessions.

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Ringkasan

Cognee provides a memory layer for AI agents through four primary operations: remember, recall, forget and improve. It supports permanent graph-backed memory and faster session memory that synchronizes to the graph. The repository also describes CLI, API server, MCP server, local UI, Docker, managed cloud and remote-server workflows. Repository metadata reports 29,718 stars, 2,872 forks and 528 open issues.

Fitur utama

  • Persistent long-term memory across agent sessions
  • Self-hosted knowledge graph construction
  • Vector embeddings combined with graph reasoning
  • Cognitive-science-grounded ontology generation
  • Permanent and session-scoped memory
  • Remember, recall, forget and improve operations
  • Automatic routing among recall strategies
  • Python API, CLI, API server and MCP server
  • Local UI and Docker deployment options
  • Claude Code and OpenClaw plugin availability
  • Official Rust and TypeScript clients
  • Local embedded development with SQLite, LanceDB and Kuzudb
  • Optional Postgres, pgvector, Neo4j, Neptune and Redis backends
  • Community adapters for Qdrant, ChromaDB, Weaviate and Milvus
  • User or tenant isolation, traceability, audit traits and OTEL collector support are described in the README

Persyaratan, instalasi, dan mulai cepat

For Python, install with `uv pip install cognee`; the README also states that pip, Poetry or another preferred Python package manager can be used. Configure `LLM_API_KEY` in the environment or copy the supplied `.env.template`. A Postgres-enabled installation is shown as `pip install "cognee[postgres]"`. Docker Compose and prebuilt `cognee/cognee:main` and `cognee/cognee-mcp:main` images are also documented.

Penggunaan

Minimal Python flow: import `cognee`, set `LLM_API_KEY`, call `await cognee.remember("Cognee turns documents into AI memory.")`, then call `await cognee.recall("What does Cognee do?")`. A `session_id` can be supplied for session memory, and `await cognee.forget(dataset="main_dataset")` removes a dataset. CLI equivalents include `cognee-cli remember`, `cognee-cli recall` and `cognee-cli forget --all`. Run `cognee-cli -ui` to open the local UI when a compatible container runtime is available.

Kompatibilitas model dan kasus penggunaan

The quick start uses an OpenAI API key as its example. The README states that other LLM providers can be integrated through provider configuration, but specific supported models and a complete provider list are not stated in the supplied repository data.

Catatan lisensi dan risiko

Repository metadata identifies the license as Apache-2.0. The README warns that using Postgres as a graph store is a demo feature and states that the production-ready Postgres graph capability is available as a licensed product.

Rilis dan pemeliharaan

No tagged release version or release changelog is included in the supplied repository record. The default branch is main, the repository is not archived, and the supplied metadata reports a last-pushed timestamp of 2026-08-03T09:10:45Z.

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