Run the cognee API server and optional interface on your own machine, check server health, connect SDK or HTTP clients, and configure authentication for personal development or use by multiple users.
中文简介正在准备中。当前显示英语简介。
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.
安装前可以查看交给 AI 代理的指令内容。
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).
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.
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, 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.
from cognee.api.v1.visualize import visualization_server
shutdown = visualization_server(port=8080) # synchronous; returns a shutdown callable
"8080:8000").ENABLE_BACKEND_ACCESS_CONTROL=false and restart.recall/search returns [] instead of erroring → permission-filtered
result; check dataset access rights for the calling user.还没有评价。欢迎分享你的使用感受。
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Operate cognee from the terminal to store, retrieve, update, and remove information. Covers dataset and configuration management, ingestion cost estimates, session history access, and commands for inspecting or applying database migrations.
中文简介正在准备中。当前显示英语简介。
Connect cognee to additional databases and data sources through community packages. The skill covers installing and registering adapters, importing data through connectors, configuring monitoring, and developing extension packages with examples and tests.
中文简介正在准备中。当前显示英语简介。
Define custom entities and relationships in cognee, a memory system for AI applications. This skill guides model design, identity matching, searchable fields, and troubleshooting when entities are duplicated or relationships are missing.
中文简介正在准备中。当前显示英语简介。
Build custom cognee processing by chaining Python tasks, defining data types, and saving results to graph and vector databases. Use it to enrich existing data, inspect run status, and troubleshoot how tasks pass data.
中文简介正在准备中。当前显示英语简介。
Run cognee in Docker, starting with a prebuilt image for local document ingestion and questions. It also covers Docker Compose profiles for adding the UI, MCP server, Postgres, and Neo4j, plus persistent data storage.
中文简介正在准备中。当前显示英语简介。
Find and remove stored content from cognee using its SDK, HTTP API, or CLI. Inspect documents before deletion, choose document or dataset removal, or keep raw files while clearing derived graph relationships and search vectors.
中文简介正在准备中。当前显示英语简介。