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@memtensor/memos-cloud-cli
Advanced tools
Universal memory interface for AI agents.
MemOS-CLI/
├── src/memos_cli/
│ ├── __init__.py # Package version
│ ├── __main__.py # python -m memos_cli entry
│ ├── main.py # Main CLI app (Typer)
│ ├── config.py # Configuration management
│ ├── output.py # Output formatting (text/json)
│ ├── branding.py # Brand colors and symbols
│ ├── state.py # State management (agent mode)
│ ├── telemetry.py # Telemetry reporting
│ ├── backend/ # API backend layer
│ │ ├── base.py # Abstract base class
│ │ └── memos_api.py # MemOS Cloud API implementation
│ └── commands/ # CLI commands
│ ├── init.py # memos init
│ ├── config_cmd.py # memos config (show/get/set)
│ └── memory.py # add/search/get/origin/delete/extract/rerank/feedback/chat
├── skills/
│ ├── memos-memory/ # Memory domain skill (P0 commands)
│ │ ├── SKILL.md # Skill entry and usage protocol
│ │ └── references/ # Skill reference docs
│ │ ├── memos-add.md
│ │ ├── memos-chat.md
│ │ ├── memos-delete.md
│ │ ├── memos-extract.md
│ │ ├── memos-get.md
│ │ └── memos-search.md
├── pyproject.toml
├── package.json
├── bin/
│ └── memos.js # npm launcher
├── scripts/
│ └── postinstall.js # npm binary installer
├── npm/
│ └── README.md # npm binary payload directory
└── README.md
npm install -g @memtensor/memos-cloud-cli@beta
The npm package downloads a prebuilt MemOS CLI binary for the current platform during installation, so end users do not need a local Python environment.
pip install -e .
npm uninstall -g @memtensor/memos-cloud-cli
memos init --agent codex
This command installs the bundled MemOS operation skill and writes the matching agent guidance.
--agent is required, and installation to a generic global directory is not supported.
--memos-plugin defaults to false. Set it to true when the target agent already has the MemOS memory plugin installed and should prefer plugin search/add flows.
It also installs shell completion automatically for the current shell when shell detection succeeds.
Supported targets:
--agent codex → ~/.codex/skills/memos/--agent cursor → ~/.cursor/skills/memos/--agent claude → ~/.claude/skills/memos/--agent openclaw → ~/.openclaw/skills/memos/--agent hermes → ~/.hermes/skills/memos/Or with arguments:
memos init --api-key YOUR_API_KEY --agent codex
memos add "User likes Python programming"
memos search "programming languages"
memos chat "What do you know about my preferences?"
memos get user_123
memos delete mem_123456
memos origin mem_123456
memos addWrite a memory into MemOS using simple text input.
Example:
memos add "User likes Python programming"
Parameters:
[MESSAGE]: Memory content to add; required; use [MESSAGE] or --message.-m, --message: Memory content to add; optional; alias of [MESSAGE]; no separate default.--user-id: User scope for the memory write; optional; defaults to configured defaults.user_id.memos searchSearch memories with semantic retrieval and optional preference/tool/skill expansion.
Example:
memos search "programming languages" --user-id user_123 --format table --detail simple
Parameters:
[QUERY]: Search query text; required; use [QUERY] or --query.-q, --query: Search query text; optional; alias of [QUERY]; no separate default.--user-id: User scope for retrieval; optional; defaults to configured defaults.user_id.--memory-limit-number: Main memory recall count; optional; defaults to 9.--include-preference: Whether to include preference memory; optional; accepts true or false; defaults to true when omitted.--preference-limit-number: Preference memory recall count; optional; defaults to 9.--include-tool-memory: Whether to include tool memory; optional; accepts true or false; defaults to false when omitted.--tool-memory-limit-number: Tool memory recall count; optional; defaults to 6.--include-skill-memory: Whether to include skill memory; optional; accepts true or false; defaults to false when omitted.--skill-memory-limit-number: Skill memory recall count; optional; defaults to 6.--relativity: Retrieval threshold; not exposed in the current CLI; API default is 0.45.--format: Output format; optional; defaults to agent.--detail: Output detail level for non-JSON formats; optional; defaults to simple; supported values: simple, detail.memos getCall the documented get_memory API to retrieve memories for a user.
Example:
memos get user_123 --format json --detail detail
Parameters:
[USER_ID]: Retrieval scope; effectively required, but if omitted the CLI falls back to configured defaults.user_id.--user-id: Alias of [USER_ID]; optional; same fallback as [USER_ID].--page: Page number; optional; API default is 1 when omitted.--size: Number of items returned per memory category on the current page; optional; API default is 10 when omitted.--include-preference: Whether to include preference memory; optional; accepts true or false; defaults to true when omitted.--include-tool-memory: Whether to include tool memory; optional; accepts true or false; current CLI exposes this flag, but the official get_memory docs do not state the API default when omitted.--format: Output format; optional; defaults to agent.--detail: Output detail level for non-JSON formats; optional; defaults to simple; supported values: simple, detail.memos deleteDelete one memory, or delete all memories for a user, using the documented delete API.
Example:
memos delete mem_123456 --format json
memos delete --user-id user_123 --format json
Parameters:
MEMORY_ID: Memory ID to delete; conditionally required; use MEMORY_ID to delete one memory.--user-id: Delete all memories for the given user ID; conditionally required; use --user-id to delete all memories for a user.memos originGet the original source payload for a specific memory by memory ID.
Example:
memos origin mem_123456
memos origin mem_123456 --detail simple
memos origin mem_123456 --detail detail
memos origin mem_123456 --format markdown --detail detail
memos origin mem_123456 --format json
Parameters:
[MEMORY_ID]: Memory ID; required.--format: Output format; optional; defaults to agent.--detail: Output detail level; optional; defaults to simple; supported values: simple, detail.Default display includes:
simple: memory_id, memory summary, and source content.detail: memory_id, memory summary, source type, role, time, language, and source content.data.metadata.sources.memos extractPreview memory candidates from messages without storing them.
Example:
memos extract "User likes coffee and prefers dark mode" --format json
Parameters:
[MESSAGE]: Message content to extract from; required; use [MESSAGE] or --message.-m, --message: Message content to extract from; optional; alias of [MESSAGE]; no separate default.--user-id: User scope; optional; defaults to configured defaults.user_id.memos rerankRerank candidate documents for a query.
Example:
memos rerank "python backend" "Flask guide" "React guide" --format json
Parameters:
[QUERY]: Query used for reranking; required; use [QUERY] or --query.[DOCUMENTS]...: Candidate documents; required; provide one or more documents as positional arguments, repeated --documents, or stdin.-q, --query: Query used for reranking; optional; alias of [QUERY]; no separate default.--documents: Candidate document, repeatable; optional; repeatable alternative to positional [DOCUMENTS]....--top-n: Return only the top N results; optional; no CLI default; omitted from the request unless provided.--format: Output format; optional; defaults to agent.memos feedbackSubmit feedback content to MemOS.
Example:
memos feedback "Prefer concise technical answers." --user-id user_123 --format json
Parameters:
[FEEDBACK_TEXT]: Feedback content to submit; required; use [FEEDBACK_TEXT] or --feedback-content.--feedback-content: Feedback content to submit; optional; alias of [FEEDBACK_TEXT]; no separate default.--user-id: User scope; optional; defaults to configured defaults.user_id.memos chatAsk MemOS for a memory-informed answer using the documented chat request fields.
Example:
memos chat "What do you know about my preferences?" --user-id user_123 --format agent
Parameters:
[QUERY]: Chat query text; required; use [QUERY] or --query.-q, --query: Chat query text; optional; alias of [QUERY]; no separate default.--user-id: User scope; optional; defaults to configured defaults.user_id.Each subcommand supports trailing --format. Only search and get also support trailing --detail:
memos search "python" --format table --detail simple
memos search "python" --format markdown --detail detail
memos search "python" --format agent --detail simple
memos search "python" --format json --detail detail
memos get user_123 --format json --detail detail
memos add "User prefers TypeScript" --format json
--api-key KEY: Override API key from config--base-url URL: Override API base URL from config--version: Show versionView current config:
memos config show
Example output includes:
API KeyBase URLSourceFrameworkUser ID and Conversation IDGet/Set specific values:
memos config get platform.api_key
memos config set defaults.user_id user123
MEMOS_API_KEY: Your API keyMEMOS_BASE_URL: API base URL (default: https://memos.memtensor.cn/api/openmem/v1)MEMOS_FRAMEWORK: Override framework attribution (for example codex)Use the provided skill to enable memory operations in your agent framework.
Use this skill when:
extract, add, search, chat, get, and delete: skills/memos-memory/SKILL.mdRecommended entry point:
skills/memos-memory/SKILL.md.All CLI requests include:
source=cli-<framework> header when the framework can be identified, for example source=cli-codexMemory API requests also attach framework metadata when it can be detected from environment variables or the parent process.
This enables usage analytics and framework-specific optimizations.
Framework detection is resolved in this order:
memos init --agent ...MEMOS_FRAMEWORKpython -m memos_cli --help
src/memos_cli/commands/src/memos_cli/main.pyFAQs
MemOS CLI - Universal memory interface for AI agents
The npm package @memtensor/memos-cloud-cli receives a total of 82 weekly downloads. As such, @memtensor/memos-cloud-cli popularity was classified as not popular.
We found that @memtensor/memos-cloud-cli demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 11 open source maintainers collaborating on the project.

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