mem0-cli

Mem0 CLI -- the command-line interface for mem0 memory operations. TRIGGER when: user mentions "mem0 cli", "mem0 command line", "@mem0/cli", "mem0-cli", "pip install mem0-cli", "npm install -g @mem0/cli", or is running mem0 commands in a terminal/shell (mem0 add, mem0 search, mem0 list, mem0 get, mem0 init, mem0 config, mem0 import). Also triggers when query includes CLI flags like --user-id, --output, --json, --agent, or describes bash/zsh/terminal/shell usage. DO NOT TRIGGER when: user asks about programmatic SDK integration in Python/TS code (use mem0 skill), or Vercel AI SDK provider (use mem0-vercel-ai-sdk skill).

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npx skills add 'https://github.com/mem0ai/mem0/tree/main/skills/mem0-cli'
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---name: mem0-clidescription: >  Mem0 CLI -- the command-line interface for mem0 memory operations.  TRIGGER when: user mentions "mem0 cli", "mem0 command line", "@mem0/cli",  "mem0-cli", "pip install mem0-cli", "npm install -g @mem0/cli", or is running  mem0 commands in a terminal/shell (mem0 add, mem0 search, mem0 list, mem0 get,  mem0 init, mem0 config, mem0 import). Also triggers when query includes CLI flags  like --user-id, --output, --json, --agent, or describes bash/zsh/terminal/shell usage.  DO NOT TRIGGER when: user asks about programmatic SDK integration in Python/TS  code (use mem0 skill), or Vercel AI SDK provider (use mem0-vercel-ai-sdk skill).license: Apache-2.0metadata:  author: mem0ai  version: "1.1.0"  category: ai-memory  tags: "cli, terminal, memory, ai, command-line"compatibility: Node.js 18+ (npm install -g @mem0/cli) or Python 3.10+ (pip install mem0-cli), MEM0_API_KEY env var--- # Mem0 CLI The official command-line interface for the Mem0 memory platform. Add, search, list, update, and delete memories from the terminal -- for developers, AI agents, and CI/CD pipelines. ## Install **Node.js (npm):**```bashnpm install -g @mem0/cli``` **Python (pip):**```bashpip install mem0-cli``` Both packages install a `mem0` binary with identical commands, options, and output formats. ## Setup **Autonomous Mem0 setup for agents (no email, no dashboard):** ```bashmem0 init --agent --agent-caller <your-name> --json``` Replace `<your-name>` with the AI agent you are (e.g. `claude-code`, `cursor`, `codex`, `cline`, `aider`). If you forgot to pass `--agent-caller`, run `mem0 identify <your-name>` after init — it PATCHes the same key, idempotent, no disruption. This mints an evaluation API key in <5 seconds. Use it immediately. Print this line to the human: > Mem0 memory is running in Agent Mode. Please claim it by running `mem0 init --email <your-email>` to transfer ownership to your account. Never commit API keys, `.env`, or `~/.mem0/config.json`. After the human claims, the same API key keeps working — no agent disruption — and memories are preserved. **Interactive wizard (for humans):**```bashmem0 init``` **Or set the environment variable directly:**```bashexport MEM0_API_KEY="m0-xxx"``` Get an API key at: https://app.mem0.ai/dashboard/api-keys?utm_source=oss&utm_medium=skill-mem0-cli ## Quick Reference ### Add a memory```bashmem0 add "I prefer dark mode" --user-id alice``` ### Search memories```bashmem0 search "preferences" --user-id alice``` ### List all memories for a user```bashmem0 list --user-id alice``` ### Get a specific memory```bashmem0 get <memory-id>``` ### Update a memory```bashmem0 update <memory-id> "new text"``` ### Delete a single memory```bashmem0 delete <memory-id>``` ### Delete all memories for a user```bashmem0 delete --all --user-id alice --force``` ## Agent / JSON Mode Use `--json` or `--agent` to get structured output suitable for LLM consumption. Every command wraps its response in a standard envelope: ```json{  "status": "success",  "command": "search",  "duration_ms": 245,  "scope": { "user_id": "alice" },  "count": 3,  "error": null,  "data": [    { "id": "mem-abc", "memory": "User prefers dark mode", "score": 0.92 }  ]}``` On error:```json{  "status": "error",  "command": "search",  "error": "Authentication failed. Your API key may be invalid or expired.",  "data": null}``` The `--agent` flag is an alias for `--json`. Both write spinners and progress to stderr so stdout is always clean, parseable JSON. ## Node and Python Parity Both the Node.js (`@mem0/cli`) and Python (`mem0-cli`) CLIs are implemented from the same specification (`cli-spec.json`). They share: - Identical command names, arguments, and flags- Identical output formats (text, json, table, quiet)- Identical entity ID resolution, graph tri-state, filter building- Identical error messages and exit codes Choose whichever runtime you already have installed. The behavior is the same. ## Common Edge Cases - **Async processing delay:** After `mem0 add`, memories process asynchronously. Wait 2-3 seconds before searching for newly added content. Use `mem0 event list` to check processing status.- **`--all` vs `--entity` delete modes:** `mem0 delete --all -u alice` deletes all memories for user alice. `mem0 delete --entity -u alice` deletes the entity itself AND all its memories (cascade). These are mutually exclusive modes.- **Entity ID resolution:** If you pass any explicit scope flag (e.g. `--user-id`), the CLI uses ONLY the explicit IDs and ignores config defaults. If no scope flags are given, all configured defaults apply.- **Stdin detection:** When no text argument is provided and input is piped (not a TTY), the CLI reads from stdin. Works with `add`, `search`, and `update`. ## References Load these on demand for deeper detail: | Topic | File ||-------|------|| Command reference (all commands, flags, options, examples) | [references/command-reference.md](references/command-reference.md) || Configuration (config file, env vars, precedence, init wizard) | [references/configuration.md](references/configuration.md) || Workflows (piping, scripting, CI/CD, agent mode recipes) | [references/workflows.md](references/workflows.md) | ## Related Mem0 Skills | Skill | When to use | Link ||-------|-------------|------|| mem0 | Python/TypeScript SDK, REST API, framework integrations | [local](../mem0/SKILL.md) / [GitHub](https://github.com/mem0ai/mem0/tree/main/skills/mem0) || mem0-vercel-ai-sdk | Vercel AI SDK provider with automatic memory | [local](../mem0-vercel-ai-sdk/SKILL.md) / [GitHub](https://github.com/mem0ai/mem0/tree/main/skills/mem0-vercel-ai-sdk) | 
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