Mmcp.market

cognee-server skill

by topoteretes·topoteretes/cognee·31k stars·Apache-2.0

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.

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Install the cognee-server skill

A skill is a folder. Copy it into your agent's skills folder and the agent loads it when the task matches its description. 

git clone --depth 1 https://github.com/topoteretes/cognee.git /tmp/cognee
mkdir -p ~/.claude/skills
cp -r /tmp/cognee/.claude/skills/cognee-server ~/.claude/skills/cognee-server
available in every project

In the Claude apps, zip the folder and upload it from the Skills settings. The folder on GitHub

The instructions your agent would load

SKILL.md as published, without the frontmatter. Read it on GitHub

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 LLMAPIKEY 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

ENABLEBACKENDACCESS_CONTROL decides everything:

user+dataset database isolation.

  • true (default): multi-tenant — auth required on every API call, per

choice for a personal dev server; never for anything exposed.

  • false: single-user local mode — no auth, shared local databases. Right

REQUIREAUTHENTICATION=false is ignored while access control is on; to turn auth off you must set ENABLEBACKENDACCESSCONTROL=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").

(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).

  • HTTP: main routes live under /api/v1/ — the memory API is remember

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

"8080:8000").

  • Port 8000 already taken → stop the other service or remap (compose:

set ENABLEBACKENDACCESS_CONTROL=false and restart.

  • 401/403 on every call → you're in multi-tenant mode; either authenticate or

result; check dataset access rights for the calling user.

  • recall/search returns [] instead of erroring → permission-filtered

More skills from topoteretes/cognee

  • Acognee-cliUse when the user wants to drive cognee from the terminal with cognee-cli — remember/recall/forget/improve memory commands, managing datasets and config, or database migrations.
  • Acognee-communityUse when the user needs something that ships outside cognee core — community database adapters (Qdrant, Milvus, Weaviate, Redis, Pinecone, FalkorDB, Memgraph, DuckDB, NetworkX, …), data-source connectors (Slack, Gmail, Notion, Confluence, Google Drive), custom tasks/pipelines/retrievers (Exa, ScrapeGraph, codify), Keywords AI observability — or wants to contribute a package to the cognee-community repo.
  • Acognee-dockerUse when the user wants to run cognee with Docker or docker compose — trying it out from the prebuilt image, starting the API server in a container, or bringing up the full stack (UI, MCP, Postgres, Neo4j) with compose profiles.
  • Acognee-installUse when the user wants to install cognee and run their first remember → recall flow with the Python SDK — fresh setup, virtual env, extras selection, or a minimal working example.
  • Acognee-integrationsUse when the user wants to connect cognee to external services — switching LLM or embedding providers (OpenAI, Azure, Gemini, Anthropic, Ollama, OpenRouter), changing databases (Postgres, PGVector, Neo4j, Neptune, Turso), S3 storage, or the MCP server for IDE integration.
  • Acognee-permissionsUse when working with cognee's permission system — understanding or changing how users, roles, and tenants get access to datasets, how ACL grants work, where permissions are enforced in add/cognify/search/delete, and how the grant records surface in the memory-provenance view.
  • Adiff-risk-explainerUse to briefly explain small code diffs.
  • Apr-comment-evaluatorUse to judge whether a PR review comment sounds polite.
  • Askill-feedback-writerUse to identify missing instructions in another skill based on its output.

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