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The command-line binary, built from the cognee-cli crate. It drives the full pipeline and is also the on-device (Android) runner. Run cognee-cli <command> --help for the authoritative flag list; the clap definitions are in crates/cli/src/cli.rs. 
cargo build --release          # produces target/release/cognee-cli

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Subcommands

The memory API verbs (remember / recall / improve / forget) are the primary surface; the add / cognify / memify / search commands below them are the lower-level pipeline they compose. All of these are always built (not feature-gated).
CommandPurposeNotable flagsFeature gate
remember <data…>Store memory: add + cognify + (by default) improve. <data…> is inline text and/or file paths-d/--dataset-name (main_dataset), --session-id, --no-improve (default OFF — improve runs by default), --tenant-id—
recall <query>Query memory with auto-routing (session-aware + graph-backed)-t/--query-type (optional — omit to auto-route), -d/--datasets (repeatable), -k/--top-k (10), --session-id, -f/--output-format (pretty/json/simple, default pretty)—
improveEnrich memory / bridge sessions (feedback + enrichment stages)-d/--dataset-name (main_dataset), --session-id (repeatable), --node-name (repeatable), --feedback-alpha (0.1), --tenant-id—
forgetRemove memory (a dataset, a single data item, or everything)-d/--dataset-name | --data-id (UUID; requires --dataset-name; conflicts with --all) | --all, --tenant-id—
add <inputs…>Ingest text / file paths / HTTP(S) URLs into a dataset-d/--dataset-name (main_dataset), --tenant-id—
cognifyBuild the knowledge graph from one or more datasets-d/--datasets, --chunk-size, --chunker (TextChunker/LangchainChunker/CsvChunker), --ontology-file, -b/--background, --llm-max-retries, --llm-max-parallel-requests, --temporal-cognify—
add-and-cognify <inputs…>add then cognify in one stepunion of the above—
memifyEnrich an existing graph with triplet embeddings-d/--datasets, --node-type, --node-name, --batch-size (100)—
search <query>Query the graph/vectors-t/--query-type (GRAPH_COMPLETION), -d/--datasets, -k/--top-k (10), --system-prompt / --system-prompt-path, --session-id, -f/--output-format (pretty/json), --llm-max-retries—
deleteRemove data/datasets across all backends-d/--dataset-name | --dataset-id, --data-id, --all, --mode (soft/hard), --dry-run, -f/--force—
config get|set|unset <key>Read/write the persisted JSON config——
run-sequenceRun a scripted add/cognify/search sequence——
visualizeRender the graph to a self-contained HTML file-o/--output (~/graph_visualization.html)visualization
benchPhase-timed benchmark driver--memories, --mock-llm, --outputbench
The feature-gated commands are enabled in the default build of cognee-cli (except platform-specific ones). See architecture.md §feature strategy. Cloud serve / disconnect are not part of OSS — they ship in the closed-source cognee-cli-cloud binary (cognee-cli-cloud serve --url … / cognee-cli-cloud disconnect).

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Memory API

The four primary verbs cover the common workflow end-to-end: 
# Store memory (add + cognify + improve). Inline text and/or file paths.
cognee-cli remember "Cognee turns data into a knowledge graph" ./notes.txt -d my_dataset

# Scope a turn to a session (session-backed memory) instead of permanent graph memory
cognee-cli remember "follow-up note" --session-id chat-42

# Query memory — omit -t to let recall auto-route the retrieval strategy
cognee-cli recall "what did we learn about X?" -d my_dataset -k 10

# Enrich memory / bridge sessions
cognee-cli improve -d my_dataset --session-id chat-42

# Remove memory
cognee-cli forget --all
cognee-cli forget -d my_dataset
cognee-cli forget --data-id 00000000-0000-0000-0000-000000000000 -d my_dataset
remember with a --session-id records session memory; without one it persists permanent, graph-backed memory. recall is session-aware and graph-backed; with no -t/--query-type it auto-routes to a suitable retrieval strategy.

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Lower-level pipeline

The memory verbs compose add → cognify → search, which you can also drive directly for fine-grained control (remember ≈ add + cognify + improve; recall ≈ auto-routed search): 
cognee-cli add ./notes.txt "some inline text" -d my_dataset
cognee-cli cognify -d my_dataset
cognee-cli search "what did we learn about X?" -t GRAPH_COMPLETION -d my_dataset -k 10

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config subcommand

Reads/writes ~/.config/cognee-rust/config.json. Keys are the snake_case Settings field names. See configuration.md §CLI config. 
cognee-cli config set llm_max_retries 4
cognee-cli config get llm_model
cognee-cli config unset embedding_endpoint

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LLM retries

--llm-max-retries N (accepted by cognify, add-and-cognify, search) overrides the retry count for structured-output LLM calls for that run; the persistent default is the llm_max_retries config key (default 2, minimum 1). The CLI flag wins over the config value. It is passed to OpenAIAdapter and governs the strict-schema, function-call, and JSON-fallback parsing paths. 
cognee-cli cognify --llm-max-retries 4
cognee-cli search "What is TechCorp?" --llm-max-retries 4

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Logging

The CLI calls cognee_logging::init_logging at startup. The env-var surface (COGNEE_LOG_*, RUST_LOG/LOG_LEVEL, LOG_FILE_NAME) is shared with the HTTP server and bindings and documented canonically in configuration.md §logging. Example — JSON logs to a custom directory: 
COGNEE_LOG_FORMAT=json COGNEE_LOGS_DIR=/var/log/cognee cognee-cli cognify -d main_dataset