cognee
Cognee - is a library for enriching LLM context with a semantic layer for better understanding and reasoning.
Decision gist · record as of 2026-08-14
Yes. Cognee is actively maintained (30023 stars, last commit 2026-08-14), has low install friction, carries no known vulnerabilities, and offers a permissive Apache-2.0 license. It solves a real problem—persistent, searchable memory for AI agents—with a mature feature set (graph + vector search, multimodal ingestion, session memory, CLI, Docker support). The 44 dependencies are substantial but justified by the full-stack nature of the platform. Install if you need agent memory infrastructure; skip if you only need lightweight semantic search or simple vector storage.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.10–3.14 and LLM_API_KEY environment variable (e.g., OpenAI API key) to function; Docker optional but recommended for the CLI UI.
- Low friction install with a pure-Python wheel.
- Active maintenance (last commit 2026-08-14) and strong community signal (30023 stars).
License · maintenance · safety
Apache-2.0 (permissive) — Apache-2.0 permissive license allows commercial use, modification, and distribution with minimal restrictions—suitable for proprietary projects and commercial deployments.
last release 2026-08-08 (6 days) · last repo commit 2026-08-14 · 30,023 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 195,178 downloads/mo, #9,820 on PyPI
Alternatives
Verify before relying
import cognee
import asyncio
async def main():
await cognee.remember("Cognee turns documents into AI memory.")
results = await cognee.recall("What does Cognee do?")
for result in results:
print(result)
asyncio.run(main())- Whether the 44 runtime dependencies can be selectively installed or if all are required for basic usage.
- Performance characteristics and scalability limits for knowledge graph size and query latency.
- Whether session memory and permanent graph storage can use different backends (e.g., local cache vs. remote database).
- Exact ontology generation mechanism and how it evolves as knowledge changes.
What it is and what it does
Cognee is an open-source AI memory platform that ingests data in any format and builds a self-hosted knowledge graph to give AI agents persistent long-term memory across sessions. It combines vector embeddings, graph reasoning, and cognitive-science-grounded ontology generation so documents are searchable by meaning and connected by relationships that evolve over time. The platform exposes four core operations—remember (store in graph), recall (query with auto-routing), forget (delete), and improve (refine)—plus a CLI and Docker deployment option. It integrates with LLM providers via LiteLLM and supports multimodal ingestion, session-scoped memory caching, and cross-agent knowledge sharing.
The package is designed for building company knowledge bases, enabling agents with domain expertise, and supporting reliable, trustworthy agent deployments with user/tenant isolation and audit trails. It runs locally by default but can be deployed as a containerized API server. The 44 runtime dependencies include FastAPI for the server, LanceDB for vector storage, Pydantic for configuration, and instructor for LLM-guided parsing; the dependency footprint is substantial but reflects a full-stack knowledge infrastructure rather than a lightweight library.
Use it for
- Build a persistent knowledge base for a multi-turn chatbot or agent that recalls context across separate conversations.
- Ingest company documents (PDFs, emails, wikis) into a unified graph and let agents query domain knowledge with semantic search.
- Integrate Cognee memory into Claude Code or other AI coding assistants to preserve coding context and decisions across sessions.
- Deploy a self-hosted knowledge graph API for multiple agents or tenants with isolated memory and audit trails.
- Prototype agentic workflows that learn from feedback and improve reasoning by connecting new insights to existing knowledge.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
Cognee is actively maintained (30023 stars, last commit 2026-08-14), has low install friction, carries no known vulnerabilities, and offers a permissive Apache-2.0 license. It solves a real problem—persistent, searchable memory for AI agents—with a mature feature set (graph + vector search, multimodal ingestion, session memory, CLI, Docker support). The 44 dependencies are substantial but justified by the full-stack nature of the platform. Install if you need agent memory infrastructure; skip if you only need lightweight semantic search or simple vector storage.
Install
cognee on PyPI
Before you install
Low friction install with a pure-Python wheel. Active maintenance (last commit 2026-08-14) and strong community signal (30023 stars). Requires Python 3.10–3.14 and 44 runtime dependencies including FastAPI, LanceDB, LiteLLM, and OpenAI; no compiled dependencies block installation.
Requires Python 3.10–3.14 and LLM_API_KEY environment variable (e.g., OpenAI API key) to function; Docker optional but recommended for the CLI UI.
License in practice
Apache-2.0 permissive license allows commercial use, modification, and distribution with minimal restrictions—suitable for proprietary projects and commercial deployments.
Quickstart
import cognee
import asyncio
async def main():
await cognee.remember("Cognee turns documents into AI memory.")
results = await cognee.recall("What does Cognee do?")
for result in results:
print(result)
asyncio.run(main())Verify before relying
- Whether the 44 runtime dependencies can be selectively installed or if all are required for basic usage.
- Performance characteristics and scalability limits for knowledge graph size and query latency.
- Whether session memory and permanent graph storage can use different backends (e.g., local cache vs. remote database).
- Exact ontology generation mechanism and how it evolves as knowledge changes.
Package facts
| License | Apache-2.0 permissive |
| Python support | Supports the current Python release <3.15,>=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 44 packagesaiofilesaiohttpaiolimiteraiosqlitealembiccbor2cryptographydatamodel-code-generatordiskcachefakeredisfastapi-usersfastapifilelockfiletypegunicorninstructorjinja2ladybuglancedblangdetectlimitslitellmnbformatnetworkxnumpyopenaipydantic-settingspydanticpylancepympler |
| Maintenance | Actively maintained 6 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 195,178 / month, #9,820 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 4 - BetaIntended Audience :: DevelopersLicense :: OSI Approved :: Apache Software LicenseOperating System :: MacOS :: MacOS XOperating System :: Microsoft :: WindowsOperating System :: POSIX :: LinuxTopic :: Software Development :: Libraries |
Evidence: cognee-1.4.2-py3-none-any.whl
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See also reme-ai · stashai · graphiti-core · hindsight-api-slim · agent-utilities · lance-context · mempalace · zep-python · gpt-researcher · mindroom