Use the cognee CLI
SkillDatabases & dataLets your agent run memory commands from the terminal to store, recall, delete, and manage knowledge datasets.
Available today. Use it from your connected AI after setup.
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Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the Use the cognee CLI skill
About this capability
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.
What this skill tells your AI
The instructions your AI receives, as published by topoteretes/cognee in .claude/skills/cognee-cli/SKILL.md and read by ahel’s review.
cognee-cli ships with the package (entry point in cognee/cli/_cognee.py;
each command lives in cognee/cli/commands/). Every command has
--help with examples — prefer that over guessing flags. Needs
LLM_API_KEY configured, same as the SDK.
Core flow
The memory commands are the primary surface as of cognee 1.x:
cognee-cli remember "Your text here" # also accepts file paths / URLs
cognee-cli remember ./docs --dataset-name my_project
cognee-cli recall "Your question" # query the graph
cognee-cli recall "keyword" --query-type CHUNKS
cognee-cli forget --all # wipe local state
remember is ingest + graph build in one step (add + cognify under the
hood); --background/-b runs the cognify stage in the background, and
--dry-run estimates LLM tokens/cost without ingesting. recall takes
--datasets/-d, --top-k/-k (default 10), and --session-id/-s.
forget targets --dataset, --dataset-id, --data-id (needs a dataset), or
--everything/--all — one unified command covering what delete, prune,
and empty_dataset used to do separately.
forget --alldoes not ask for confirmation. It deletes every dataset immediately, even on a non-interactive stdin. The legacydelete --allpromptsDelete ALL data from cognee? [y/N]first, so switching toforgetsilently drops that safety net — script it with care.
Search types match exactly 7 of the SDK's SearchType enum (cognee/modules/search/types/SearchType.py), those 7 being chosen in (cognee/cli/config.py:SEARCH_TYPE_CHOICES):
GRAPH_COMPLETION, RAG_COMPLETION, CHUNKS, SUMMARIES, CODE, CYPHER, GRAPH_REPORT
Others must be reached from the SDK, not CLI; e.g. call cognee.recall with query_type=SearchType.TEMPORAL
Note the CLI defaults --query-type to GRAPH_COMPLETION, whereas the SDK's
cognee.recall() auto-routes when query_type is omitted.
Session memory and enrichment
Session entries are currently written from the SDK — cognee.remember(..., session_id="chat_1") — not the CLI (cognee-cli remember has no session
flag). The CLI side of session memory is reading and bridging:
cognee-cli recall "question" -s chat_1 # session cache first: without -d/-t
# this searches the session directly
cognee-cli sessions get # retrieve session Q&A history
cognee-cli improve -d my_project -s chat_1 # bridge session content into the graph
cognee-cli improve -d my_project # enrich/index the graph (no session)
cognee-cli feedback ... # attach feedback to results
improve also takes --node-name, --feedback-alpha (default 0.1), and
--background/-b. remember/improve build their graphs through
cognify(), so cognify-level settings (e.g. CONTRADICTION_DETECTION=true)
apply to them too.
Legacy / lower-level commands
add, cognify, search, memify, and delete still ship and are what the
memory commands call underneath. Use them only to drive a single stage in
isolation; prefer remember/recall/forget/improve otherwise.
cognee-cli add "text" && cognee-cli cognify # what `remember` does in one step
cognee-cli search "question" # `recall` minus routing/scope/session sources
cognee-cli memify -d my_project # custom extraction/enrichment tasks
cognee-cli delete --all # superseded by `forget --all`
Management
cognee-cli datasets list # dataset operations
cognee-cli config get [key] [--show-secrets] # view one/all settings (API keys masked by default)
cognee-cli config set <key> <value> # set + persist to ./.env in the cwd
cognee-cli config unset <key> # reset a key to its default (also persisted)
cognee-cli -ui # launch API server + UI (see cognee-server skill)
cognee-cli serve --url http://localhost:8000 # connect CLI/SDK to a running instance
Relational DB migrations (Alembic)
cognee-cli upgrade # apply migrations
cognee-cli downgrade
cognee-cli history
cognee-cli current
Typically needed after version upgrades when the server refuses to start on an old schema.
Gotchas
- The CLI initializes cognee lazily; the first command in a fresh environment is slow (DB + model setup), later ones are fast.
remember(andadd) without--dataset-nametargets the default datasetmain_dataset;recall/searchoperate across your accessible datasets unless a dataset is given.forgetrefuses to run bare — pass--dataset,--dataset-id,--data-id(with a dataset), or--everything/--all.- Session commands (
recall -s,sessions get,improve -s) requireCACHING=true(the default) — with it off, session reads return nothing and SDK session writes raise. To cut read latency and token cost while keeping session memory,cognee-cli config set AUTO_FEEDBACK false— by default cognee makes one structured-output LLM call per answered query to self-tune its memory. memifyrequires one of the arguments -d/--dataset-name --dataset-idconfig set/config unsetwrite to the.envfile in whatever directory you run the command from (creating it if missing).config reset(reset all keys) is still not implemented.- Which
.envactually wins is not always the cwd one. At import, cognee callsdotenv.load_dotenv(override=True), which resolves relative to the cognee package location, not your working directory. In a source/editable checkout (uv pip install -e .) a.envat the repo root therefore shadows the.envin the directory you ran from — and becauseoverride=True, it also beats variables youexported. Symptom:config setappears to do nothing, or the CLI connects to a backend you thought you had overridden. To test against different settings, move the repo.envaside, or set values programmatically after import (cognee.config.set_*). (Underpython -cthe cwd.envdoes win, because dotenv falls back to the cwd when__main__has no__file__— which is why the same command can behave differently as a script vs.-c.)
Signals
- GitHub stars
- 31k
- Forks
- 3k
- Last commit
- Sep 2026
ahel review
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cognee-cli- Source
- github.com/topoteretes/cognee