mindmemos-cli

ソース文書であり、このサイトへの操作指示ではありません。コマンド実行前に権限を確認してください。

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

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

mindmemos config show          # masked key, base_url, user_id
mindmemos memory search "test" # confirms connectivity with a project-wide search

# 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

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 --token-budget 2000 --user-id alice --json
# project-wide search across all users in the API-key project
mindmemos memory search "project notes" --filter '{"memory_type":"semantic"}'

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

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

mindmemos memory feedback \
  --text "the lunch recommendation was wrong; user dislikes spicy food" \
  --messages-json '[{"role":"user","content":"I do not like spicy food."}]'

mindmemos memory feedback \
  --text "the coffee preference was wrong" \
  --messages-json-file turn.json \
  --recalled-memories-json '[{"id":"mem_123","memory":"User prefers hot coffee."}]'

mindmemos memory feedback   # omit --text: server analyzes recent adds

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

name: mindmemos-cli
description: Give an AI agent persistent, cross-session long-term memory through MindMemOS. Covers installing and authenticating the mindmemos CLI, the full command interface (add / search / get / update / delete / feedback / dreaming) with parameters and examples, guidance on which capability to use when, plus a Python SDK example. To wire memory into a specific agent host (OpenClaw, DeepSeek Harness, Codex, Claude, etc.), see references/.

---
name: mindmemos-cli
description: Give an AI agent persistent, cross-session long-term memory through MindMemOS. Covers installing and authenticating the mindmemos CLI, the full command interface (add / search / get / update / delete / feedback / dreaming) with parameters and examples, guidance on which capability to use when, plus a Python SDK example. To wire memory into a specific agent host (OpenClaw, DeepSeek Harness, Codex, Claude, etc.), see references/.
---

# 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](#host-integrations).

---

## Install the CLI

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

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

Authenticate once. This writes a local config (API key, default user id, base URL). Operations that require a
user inherit the default user id, but `memory search` does not: omit `--user-id` for project-wide search or pass
it explicitly for user-scoped search.

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

Verify:

```bash
mindmemos config show          # masked key, base_url, user_id
mindmemos memory search "test" # confirms connectivity with a project-wide search
```

---

## 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. For `memory search`, `--user-id`
is per-request and does not inherit the user configured by `mindmemos auth`.

### 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).

| Option | Meaning |
|---|---|
| `--content TEXT` | single message body (paired with `--role`) |
| `--role {user,assistant,system,tool}` | role for `--content` (default `user`) |
| `--messages-json '[...]'` | JSON array of messages; overrides `--content` |
| `--messages-json-file PATH` | read the JSON array from a file (`-` = stdin) |
| `--user-id`, `--app-id`, `--agent-id`, `--session-id` | scoping |
| `--metadata-json '{...}'` | business metadata object |
| `--skill-context-json '[...]'` | explicit skill trace context |
| `--async` | enqueue and return immediately (no extracted memories in response) |
| `--json` | machine-readable output |

```bash
# 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

Use before answering or acting when the agent needs prior user preferences,
project facts, decisions, or past experience related to the current request.

| Option | Meaning |
|---|---|
| `query` (positional) | search text |
| `--top-k N` | results to return (default 10) |
| `--search-strategy {fast,agentic}` | `fast` = vector recall; `agentic` = multi-step reasoning over memory |
| `--rerank` | rerank candidates for precision |
| `--score-threshold N` | minimum rerank relevance score (0–1); only effective with `--rerank` |
| `--token-budget N` | strict token budget for the result set; enables token-budget retention (packing under a token limit) — the result is still capped by `--top-k`, whichever limit is tighter |
| `--filter '{...}'` | structured filter DSL, JSON object (e.g. `{"memory_type":"semantic"}`) |
| `--user-id`, `--app-id`, `--agent-id`, `--session-id` | scoping; omit `--user-id` for project-wide search |
| `--json` | machine-readable output |

```bash
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 --token-budget 2000 --user-id alice --json
# project-wide search across all users in the API-key project
mindmemos memory search "project notes" --filter '{"memory_type":"semantic"}'
```

### `memory get` — list / filter (no query)

Use for inspection, audits, dashboards, or manual curation when you need to
enumerate stored memories rather than search by semantic relevance.

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

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

### `memory update` / `memory delete` — correct by id

Use `memory update` when a specific memory id is known and the stored content
should be rewritten because it is stale, incomplete, or partially wrong.

Use `memory delete` when a specific memory id is known and the memory should be
removed because it is invalid, duplicated, sensitive, or no longer appropriate.

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

### `memory feedback` — reinforce / correct memory quality

Use feedback after an outcome reveals whether recalled memory was helpful,
missing, stale, or wrong; choose explicit or implicit mode based on whether the
caller can provide the interaction context.

Feedback has two modes:

| Mode | When to use | Required context |
|---|---|---|
| Explicit feedback (`--text`) | Use when the user or host has a concrete correction or quality signal about a specific interaction, such as "that recalled preference was wrong." | Must include `--messages-json` or `--messages-json-file`; include recalled memories when available. |
| Implicit feedback (no `--text`) | Use when the service should mine recent add records and interaction traces for feedback signals without a caller-written correction. | No messages are passed on the CLI; the server derives context from recent records. |

| Option | Meaning |
|---|---|
| `--text TEXT` | explicit feedback text; requires message context |
| `--messages-json '[...]'` | JSON array of messages from the feedback round |
| `--messages-json-file PATH` | read feedback messages from a file (`-` = stdin) |
| `--recalled-memories-json '[...]'` | optional JSON array of memories recalled in that round |
| `--recalled-memories-json-file PATH` | read recalled memories from a file (`-` = stdin) |
| `--user-id`, `--app-id`, `--agent-id`, `--session-id` | scoping |

```bash
mindmemos memory feedback \
  --text "the lunch recommendation was wrong; user dislikes spicy food" \
  --messages-json '[{"role":"user","content":"I do not like spicy food."}]'

mindmemos memory feedback \
  --text "the coffee preference was wrong" \
  --messages-json-file turn.json \
  --recalled-memories-json '[{"id":"mem_123","memory":"User prefers hot coffee."}]'

mindmemos memory feedback   # omit --text: server analyzes recent adds
```

### `memory dreaming` — consolidation pass

Use as a scheduled or background maintenance step to consolidate, merge,
compress, or reorganize accumulated memories outside the hot request path.

| Option | Meaning |
|---|---|
| `--sync` | run synchronously |
| `--async` | enqueue asynchronously (default) |
| `--user-id`, `--app-id`, `--agent-id`, `--session-id` | scoping |

```bash
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.

---

## Capabilities — when to use what

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

| Intent | Use | Notes |
|---|---|---|
| "Remember this" — a new fact, preference, or conversation turn surfaced | **`add`** | Server extracts durable facts and dedups/merges against existing memory. Prefer passing real conversation messages over hand-written summaries. |
| "What do I already know about X?" — pull context before answering | **`search`** | Relevance-ranked. `fast` for latency-sensitive recall; `agentic` when the answer requires reasoning across several memories; add `--rerank` when precision matters more than speed. |
| "Show me everything in this project / a slice of it" | **`get`** | Filter/enumerate without a query; for inspection, audits, dashboards. |
| "This stored memory is stale or partly wrong" | **`update`** | Rewrite one known `memory_id` while keeping the memory as the corrected canonical record. |
| "This stored memory should not exist" | **`delete`** | Remove one known `memory_id` when the memory is invalid, duplicated, sensitive, or inappropriate to keep. |
| "The last recall was wrong/helpful/missing something" — the caller can provide the interaction context | **explicit `feedback --text`** | Pass `--messages-json` or `--messages-json-file`; pass recalled memories too when available so the planner can target the right memory. |
| "Review recent memory operations for quality signals" — no explicit correction text is available | **implicit `feedback`** | Omit `--text`; the server analyzes recent add records and traces itself. |
| "Consolidate in the background" — compress, link, reorganize accumulated memory | **`dreaming`** | An offline maintenance pass with no inputs. Run periodically (e.g. scheduled), not per-turn. |

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 p