Start the cognee server locally

SkillDev tools

Lets your agent start and check the cognee API server on your machine and connect clients to it.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the Start the cognee server locally skill

About this capability

Use when the user wants to run the cognee API server (and optional UI) on their own machine — starting it, checking it's healthy, connecting the SDK or other clients to it, and choosing the right auth posture.

What this skill tells your AI

The instructions your AI receives, as published by topoteretes/cognee in .claude/skills/cognee-server/SKILL.md and read by ahel’s review.

From an installed cognee (no Docker)

cognee-cli -ui

launches the full local stack: FastAPI backend on http://localhost:8000 and the UI on http://localhost:3000. Needs LLM_API_KEY in the environment or .env. The interactive API reference is at http://localhost:8000/docs, health at /health.

For API-only serving via Docker instead, use the cognee-docker skill (the prebuilt cognee/cognee:main image or docker compose up from the repo).

Auth posture

ENABLE_BACKEND_ACCESS_CONTROL decides everything:

  • true (default): multi-tenant — auth required on every API call, per user+dataset database isolation.
  • false: single-user local mode — no auth, shared local databases. Right choice for a personal dev server; never for anything exposed.

REQUIRE_AUTHENTICATION=false is ignored while access control is on; to turn auth off you must set ENABLE_BACKEND_ACCESS_CONTROL=false.

Connecting clients to the running server

  • SDK / CLI against the server (instead of embedded local mode):

    cognee-cli serve --url http://localhost:8000        # local instance
    cognee-cli serve                                    # cognee cloud (device flow)
    cognee-cli serve --logout                           # disconnect
    

    In Python: await cognee.serve(url="http://localhost:8000").

  • HTTP: main routes live under /api/v1/ — the memory API is remember (plus remember/entry), recall, improve, forget; sessions covers session memory; datasets, users, visualize handle the rest. The legacy add, cognify, search, memify, and delete routes still exist and are what the memory routes call underneath (see cognee/api/client.py for the registered routers, or GET /openapi.json on a running server).

    Note there is no /api/v1/feedback routefeedback exists as a CLI command and in the SDK, but is not exposed over HTTP.

Graph visualization without the full UI

from cognee.api.v1.visualize import visualization_server

shutdown = visualization_server(port=8080)  # synchronous; returns a shutdown callable

Troubleshooting

  • Port 8000 already taken → stop the other service or remap (compose: "8080:8000").
  • 401/403 on every call → you're in multi-tenant mode; either authenticate or set ENABLE_BACKEND_ACCESS_CONTROL=false and restart.
  • recall/search returns [] instead of erroring → permission-filtered result; check dataset access rights for the calling user.

Signals

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Last commit
Sep 2026
Advanced
Catalog kind
skill
Gateway key
cognee-server
Source
github.com/topoteretes/cognee