
Run cognee in Docker
Start the cognee memory server in Docker, from a prebuilt image or the full repo stack.
- Repository
- topoteretes/cognee
- Stars
- 33,002
- Licence
- Apache-2.0
- Files
- 1 file
What it does
When installed, the agent knows how to start cognee, a tool that turns documents into AI memory, inside Docker containers. It can write a minimal docker-compose file that pulls the prebuilt image, guide you through starting the API server and sending a first note and query, or bring up the fuller repository stack with optional UI, MCP server, Postgres and Neo4j profiles. It is a setup guide: it tells the agent which commands and settings to use rather than doing new analysis itself.
Great for
- Developers who want to try cognee locally without cloning or building the code
- Teams setting up a shared cognee server with optional UI, MCP or databases via Docker Compose
Skip it if
- Production deployments: the try-out config disables access control and uses shared local databases with default credentials, so it is not suitable as-is for real data
- Users without Docker or without an OpenAI (or other LLM) API key, since the setup cannot run without them
Try asking
- “Set up cognee in Docker so I can test it on my own documents”
- “Start the cognee API server in a container and show me how to send a test note and query it”
- “Bring up the full cognee stack with the UI and Postgres using docker compose profiles”
Install in 3 steps
- 1
Download the skill
The ZIP contains the 1 original files, the Apache-2.0 licence and an attribution note.
cognee-docker.zip - 2
Add it to your agent
Claude Code (all projects)
mkdir -p ~/.claude/skills && unzip cognee-docker.zip -d ~/.claude/skills/Claude Code / Agent SDK (this project only)
mkdir -p .claude/skills && unzip cognee-docker.zip -d .claude/skills/Claude apps (web/desktop): Settings → Capabilities → Skills → Upload skill, and choose the ZIP.
- 3
Ask for the task
No special command needed — the agent reads the skill's description and loads it when your request matches. Try one of the prompts above.
Get better results
- Keep the try-out setup on a local machine; change the default Neo4j and Postgres passwords before any shared use
- Set ENABLE_BACKEND_ACCESS_CONTROL appropriately if more than one person uses the server, since leaving it unset requires authentication on every call
- Store your API key in a .env file or environment variable rather than pasting it into chat or committing it to version control
What's inside
- SKILL.md
Redistributed unmodified from topoteretes/cognee under the Apache-2.0 licence. The assessment was drafted with AI from the skill's files on 2026-10-29. Skills can instruct your agent to run code — read SKILL.md and any scripts before installing.