mindmemos-cli

MindMemOS CLI

MindMemOS is a long-term memory layer for AI agents. The mindmemos CLI is the integration surface: every memory operation is a subcommand that prints either a human-readable line or, with --json, stable machine-readable output. Any agent or script can drive memory by shelling out to it.

To connect memory to a specific agent host (e.g. an editor or assistant that supports plugins), the host calls this same CLI. Host-specific install guides live under references/ — see Host integrations.

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Install the CLI

The CLI ships as the Python package mindmemos and exposes a mindmemos executable.

pip install mindmemos
# or, isolated so it's on PATH globally (recommended):
pipx install mindmemos
uv tool install mindmemos

Authenticate once. This writes a local config (API key, default user id, base URL):

mindmemos auth
# non-interactive:
mindmemos auth --api-key sk-... --user-id alice --base-url https://api.mindmemos.example.com

Verify:

mindmemos config show          # masked key, base_url, user_id
mindmemos memory search "test" # confirms connectivity

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CLI interface

General shape: mindmemos <group> <command> [args] [options].

• Memory commands do not accept a caller-provided request ID. The server generates request_id and includes it in command responses for tracing.
• search / add support --json for stable machine-readable output (what scripts and host integrations parse).
• Exit codes: 0 = success, 1 = API/config error, 2 = bad arguments. On non-zero exit the error text (including server stderr) is printed to stdout/stderr.

Identity & scoping options (where accepted): --user-id (the human the memory belongs to), --app-id, --agent-id, --session-id. Project isolation is derived from the API key, not from these flags.

Typical flow

1. mindmemos auth once.
2. During a session: memory search to recall, memory add to store turns.
3. Maintenance / background: memory get to inspect, memory update / memory delete to correct, memory feedback and memory dreaming to let the system consolidate.

memory add — store new memory

Extracts durable facts from messages and persists them (with dedup/merge against existing memory).

# single line
mindmemos memory add --content "I'm allergic to peanuts" --user-id alice

# a conversation turn
mindmemos memory add --messages-json \
  '[{"role":"user","content":"book me a window seat next time"},
    {"role":"assistant","content":"Noted, window seats going forward."}]' \
  --session-id sess-42 --json

# fire-and-forget
mindmemos memory add --content "prefers dark mode" --async

memory search — recall by relevance

mindmemos memory search "what are the user's dietary restrictions?" --top-k 5 --user-id alice
mindmemos memory search "travel prefs" --rerank --search-strategy agentic --json
mindmemos memory search "notes" --filter '{"memory_type":"semantic"}'

memory get — list / filter (no query)

Returns memories in the current project, optionally filtered. Carries no actor identity — project scope comes from the API key.

mindmemos memory get --filter '{"app_id":"openclaw"}' --top-k 20

memory update / memory delete — correct by id

mindmemos memory update mem_123 --content "allergic to peanuts and shellfish"
mindmemos memory delete mem_123 --yes

memory feedback — reinforce / correct memory quality

mindmemos memory feedback --text "the lunch recommendation was wrong; user dislikes spicy food"
mindmemos memory feedback   # omit --text: server analyzes recent adds

memory dreaming — consolidation pass

mindmemos memory dreaming
mindmemos memory dreaming --sync --app-id openclaw

Other groups

• mindmemos auth / config show [--show-secret] / config reset [-y] — credentials & local settings.
• mindmemos skill <register|list|show|pull|push|update|rollback|history|diff|unregister> — SDK-managed skills. Use register <skill_dir_or_SKILL.md> --alias <alias> to save a local alias, then use that alias anywhere a skill id is accepted. Use push <skill> after editing local SKILL.md to upload a new version. Use update <skill|--all> [--yes] to checkout published heads, rollback <skill> --to <version_id> [--yes] to restore a cached/downloaded version after reviewing the replacement plan, and diff <skill> [--from <version_id>] --to <version_id> for a read-only unified diff.
• mindmemos memory add ... --skill-context-json '[...]' — optional explicit skill trace context. When omitted, the SDK has a best-effort fallback for OpenClaw-style SKILL.md tool-call text in the add messages; host integrations such as the OpenClaw plugin may still provide their own detection and pass this flag explicitly.
• mindmemos doctor — config/connectivity check.

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Capabilities — when to use what

MindMemOS is a memory lifecycle, not just a key-value store. Pick the operation by intent:

Rules of thumb:

• add + search are the hot path — almost every agent turn does one or both.
• feedback and dreaming are the slow path — they improve memory quality over time. feedback is event-driven (an outcome happened); dreaming is schedule-driven (periodic consolidation), not for a hot request path.
• update / delete / get are manual curation — fixing mistakes and inspecting state, usually by a human or an admin tool, not in normal conversation flow.
• Always scope writes and reads with a stable --user-id (and --session-id where it matters) so memories don't leak across users.

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Calling from Python

When memory operations live inside a Python agent/app rather than a shell call, use the SDK shipped in the same mindmemos package (same API, same mindmemos auth config). See references/python-sdk.md for the full sync + async example. Minimal sync usage:

from mindmemos_sdk import MindMemOSClient, DialogueMessage

with MindMemOSClient(user_id="alice") as client:   # reads `mindmemos auth` config
    client.memory.add(messages=[DialogueMessage(role="user", content="allergic to peanuts")])
    hits = client.memory.search("dietary restrictions", top_k=5)
    for hit in hits.memories:
        print(hit.id, hit.memory)

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Host integrations

To wire MindMemOS into an agent host so memory is recalled and stored automatically (rather than calling the CLI by hand), follow the host-specific guide. All hosts depend on the CLI installed and authenticated above.

• OpenClaw — references/openclaw-plugin.md
• Codex — planned
• Claude — planned