Use 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.
日本語の概要は準備中です。原文の説明を表示しています。
topoteretes/cognee3.2万2026年10月10日 更新
無料GitHub で公開
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.
含まれるファイル（1）
- SKILL.md2.8 KB
SKILL.md（原文）
インストールする前に、エージェントに与えられる指示の中身を確認できます。
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 # disconnectIn Python:
await cognee.serve(url="http://localhost:8000"). -
HTTP: main routes live under
/api/v1/— the memory API isremember(plusremember/entry),recall,improve,forget;sessionscovers session memory;datasets,users,visualizehandle the rest. The legacyadd,cognify,search,memify, anddeleteroutes still exist and are what the memory routes call underneath (seecognee/api/client.pyfor the registered routers, orGET /openapi.jsonon a running server).Note there is no
/api/v1/feedbackroute —feedbackexists 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=falseand restart. recall/searchreturns[]instead of erroring → permission-filtered result; check dataset access rights for the calling user.
レビュー
まだレビューはありません。使ってみた感想をお寄せください。
同じリポジトリのスキル
概要と使いどころ
Use 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.
日本語の概要は準備中です。原文の説明を表示しています。
topoteretes/cognee3.2万2026年10月10日 更新
Use when defining the shape of cognee's knowledge graph with graph_model= — writing DataPoint node classes, choosing identity and index fields so nodes merge and are searchable, declaring typed Edge fields and FromIdentity references, building a model from a JSON schema, or debugging duplicated nodes, missing edges, or InvalidReferenceTypeError.
日本語の概要は準備中です。原文の説明を表示しています。
topoteretes/cognee3.2万2026年10月10日 更新
Use when building your own cognee processing — writing custom tasks, chaining them into a pipeline with run_custom_pipeline or the lightweight run_pipeline (from cognee.pipelines import run_pipeline), storing custom DataPoints with add_data_points, running custom extraction/enrichment over the existing graph with memify, checking pipeline run status, or debugging how data flows between tasks (batch_size, data_per_batch, ctx, Drop, enriches).
日本語の概要は準備中です。原文の説明を表示しています。
topoteretes/cognee3.2万2026年10月10日 更新
Use 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.
日本語の概要は準備中です。原文の説明を表示しています。
topoteretes/cognee3.2万2026年10月10日 更新
Use when removing data from cognee memory with forget() in the SDK, HTTP API, or CLI — finding which dataset and document hold the content to delete (listing datasets and data items, reading raw content), choosing between deleting one document, a whole dataset, or only the graph/vector memory, and doing it safely.
日本語の概要は準備中です。原文の説明を表示しています。
topoteretes/cognee3.2万2026年10月10日 更新