How do I install the Cognee Server skill?

Run npx skillmds add topoteretes/cognee-server in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Cognee Server safe to use?

This skill has not completed SkillMD's automated safety review yet. Capability flags: makes network calls. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Cognee Server?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Cognee Server free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Cognee Server?

topoteretes (@topoteretes) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Cognee Server by topoteretes — Agent Skill

Name: Cognee Server
Rating: 4.2 (5 reviews)
Author: topoteretes

Cognee Server

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.

topoteretes c023013 2.8 KB Updated Sep 9, 2026

File contents

Start the cognee server locally

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 route — feedback 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.

---name: cognee-serverdescription: 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.--- # Start the cognee server locally ## From an installed cognee (no Docker) ```bash 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): ```bash 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` route** — `feedback` exists as a CLI command and in the SDK, but is not exposed over HTTP. ## Graph visualization without the full UI ```python 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.

Frequently asked questions