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Mem0
by
Abhay Bhat
· GitHub ↗
· v1.0.0
2309
Downloads
3
Stars
23
Active Installs
1
Versions
Install in OpenClaw
/install mem0
Description
Intelligent memory layer for Clawdbot using Mem0. Provides semantic search and automatic storage of user preferences, patterns, and context across conversati...
Usage Guidance
Before installing, be aware this skill expects you to run Node scripts and to provide an OPENAI_API_KEY (even though the registry metadata omits them). It will create a local DB under ~/.mem0 and send text to OpenAI for embeddings and extraction. Recommended steps: (1) only install if you are willing to provide an OpenAI key and allow local persistent storage; (2) run the package in an isolated environment and npm install the dependencies yourself (review package-lock); (3) consider creating an OpenAI key with limited scope or billing limits; (4) change the hardcoded USER_ID and review what memory types will be stored (avoid storing secrets); (5) if you need the skill to be non-autonomous, ensure agent invocation policies prevent automatic runs. The primary issues are metadata omissions (Node and OPENAI_API_KEY) and lack of an install procedure — these should be resolved or understood before trusting the skill.
Capability Analysis
Type: OpenClaw Skill
Name: mem0
Version: 1.0.0
The OpenClaw AgentSkills skill bundle 'mem0' is classified as benign. Its purpose is to provide an intelligent memory layer for an AI agent using the `mem0ai` library. The `SKILL.md` instructions are clear, align with the stated purpose, and explicitly advise against storing sensitive information like secrets or API keys. The Node.js scripts (`mem0-add.js`, `mem0-config.js`, `mem0-delete.js`, `mem0-list.js`, `mem0-search.js`) handle local file operations (writing to `~/.mem0/history.db`) and use environment variables (`OPENAI_API_KEY`) for API access, which are standard and expected practices. There is no evidence of intentional data exfiltration, malicious execution, persistence mechanisms, or harmful prompt injection attempts within the provided files.
Capability Assessment
Purpose & Capability
The skill's name/description match the code: it implements a mem0 memory layer. However the registry metadata claims no required env vars and no required binaries, while the scripts and SKILL.md clearly require Node.js and an OPENAI_API_KEY. That mismatch is unexplained and disproportionate to the documented purpose (the skill legitimately needs the OpenAI key and node runtime but failed to declare them).
Instruction Scope
SKILL.md instructions stay on-topic (search before responding, add/list/delete memories). They instruct running the included Node scripts which call mem0 APIs and use the OPENAI_API_KEY for embeddings and extraction. Instructions also instruct storing a SQLite DB under ~/.mem0/history.db; that's within scope for a memory layer but is a persistence and privacy consideration. There are no obvious instructions to read unrelated system files or exfiltrate data to unexpected endpoints.
Install Mechanism
This is marked as an instruction-only skill (no install spec), yet the package.json/package-lock and scripts indicate Node code with an npm dependency (mem0ai). The skill does not declare that Node or npm must be available, nor does it provide an install step for dependencies. That makes the runtime behavior unclear and could surprise users (scripts will fail or behave inconsistently if dependencies are not installed).
Credentials
The code and SKILL.md explicitly require OPENAI_API_KEY (and optionally JSON_OUTPUT env var) but the registry metadata lists no required environment variables or primary credential. Requesting an OpenAI API key is reasonable for this function, but it must be declared. The scripts also default to a hardcoded USER_ID 'abhay', which is an odd/poorly generalized default and may expose or entrench a specific identity in a shared environment.
Persistence & Privilege
The skill writes persistent files to the user's home directory (~/.mem0/history.db) and uses a local vector store. That persistence is expected for a memory layer. always is false and the skill does not request system-wide config changes or other skills' credentials. Still, persistent local storage and autonomous model invocation (allowed by platform defaults) mean the skill can repeatedly access and store user data during use.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install mem0 - After installation, invoke the skill by name or use
/mem0 - Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
Initial release of mem0: an adaptive conversational memory layer for Clawdbot.
- Adds semantic search and automatic memory storage of user preferences, patterns, and conversational context.
- Supports explicit memory commands (e.g. "remember this"), adaptive learning from conversations, and semantic recall for personalized responses.
- Provides CLI tools for searching, adding, listing, and deleting memories.
- Complements Clawdbot's structured MEMORY.md with dynamic, learned context.
- Achieves improved accuracy and efficiency over basic context retrieval methods.
Metadata
Frequently Asked Questions
What is Mem0?
Intelligent memory layer for Clawdbot using Mem0. Provides semantic search and automatic storage of user preferences, patterns, and context across conversati... It is an AI Agent Skill for Claude Code / OpenClaw, with 2309 downloads so far.
How do I install Mem0?
Run "/install mem0" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is Mem0 free?
Yes, Mem0 is completely free (open-source). You can download, install and use it at no cost.
Which platforms does Mem0 support?
Mem0 is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created Mem0?
It is built and maintained by Abhay Bhat (@abhayjb); the current version is v1.0.0.
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