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mem0 Local Memory
作者
dream-star-end
· GitHub ↗
· v1.2.0
· MIT-0
128
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1
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0
当前安装
4
版本数
在 OpenClaw 中安装
/install mem0-local-memory
功能描述
Local long-term memory plugin for OpenClaw using mem0 + ChromaDB. Gives all agents persistent cross-session semantic memory with auto-recall and auto-capture...
安全使用建议
Before installing: (1) Understand the data flow — the import script will read MEMORY.md and TOOLS.md from multiple ~/.openclaw/workspace-* directories and POST snippets to the local mem0 server; that server will send text to DeepSeek and DashScope (third-party services). Review those workspace files and remove any secrets or sensitive content first. (2) Metadata mismatch: the registry claims no required env vars but SKILL.md requires MEM0_LLM_API_KEY and MEM0_EMBEDDER_API_KEY — expect to provide those. (3) Avoid placing API keys in world-readable systemd/plist files; limit file permissions or use a secure secret mechanism. (4) Confirm requirements.txt in the upstream repo before running setup.sh; consider running setup inside an isolated VM/container first. (5) If you need stricter privacy, consider replacing third-party embedder/LLM with a local-only option or ensure you trust DeepSeek/DashScope's data handling policy. (6) If you proceed, run the import script only after auditing and optionally editing the WORKSPACES dict to import selectively rather than everything.
能力评估
Purpose & Capability
The declared purpose (local mem0 memory using DeepSeek for LLM extraction, DashScope for embeddings, and ChromaDB for storage) matches the instructions and included scripts. However the registry metadata lists no required environment variables or primary credential while the SKILL.md explicitly requires DeepSeek and DashScope API keys — an incoherence between metadata and runtime requirements.
Instruction Scope
Runtime instructions and the import script read MEMORY.md and TOOLS.md from multiple ~/.openclaw/workspace-* directories and POST parsed text to the mem0 server (which in turn uses third‑party DeepSeek/DashScope APIs). This is in-scope for 'import memories' but is high-risk privacy-wise: it aggregates data across agent workspaces, unifies user_id to 'openclaw' (removing per-agent isolation), and sends text snippets to external APIs. SKILL.md warns the user, but the script will import everything by default unless manually edited.
Install Mechanism
There is no platform install spec (instruction-only), which keeps risk lower. The included setup.sh creates a Python venv and runs pip install -r requirements.txt. The requirements.txt file is not present in the provided package snapshot (inconsistency) — installation will pull packages from PyPI (mem0ai, chromadb, flask, openai mentioned). This is expected but grants network access and executes third-party code.
Credentials
The skill legitimately needs DeepSeek and DashScope API keys for its stated LLM/embedding tasks, and the SKILL.md asks the user to set MEM0_LLM_API_KEY and MEM0_EMBEDDER_API_KEY. However the registry metadata did not declare these env vars (metadata mismatch). The instructions also show placing keys directly into systemd/launchd service files (plaintext in unit/plist), which can expose secrets if those files are accessible. The import script uses MEM0_URL env var (default 127.0.0.1) — if altered, it could cause memories to be POSTed to a remote endpoint.
Persistence & Privilege
The skill does not request always:true and is user-invocable; it suggests installing a long-running mem0 server via launchd or systemd, which is expected for a local memory service. That does require storing API keys or environment variables in persistent service configuration (systemd/unit/plist), which increases exposure if service files are misconfigured or world-readable. Autonomous invocation is allowed by default (normal for skills) and not by itself a sufficient concern.
如何使用
- 确保已安装 OpenClaw（本地或 Docker 部署）
- 在对话框中输入安装命令：
/install mem0-local-memory - 安装完成后，直接呼叫该 Skill 的名称或使用
/mem0-local-memory触发 - 根据 Skill 的参数说明提供必要输入，即可获得结构化输出
版本历史
v1.2.0
Address security scan: declare DeepSeek/DashScope API key requirements in description, add privacy notices for import script and external API calls
v1.1.0
English description + self-install guide for OpenClaw agents + GitHub star CTA
v1.0.1
Initial release: local mem0 memory system for OpenClaw with DeepSeek LLM + DashScope embedding + ChromaDB
v1.0.0
Initial release: local mem0 memory system for OpenClaw
元数据
常见问题
mem0 Local Memory 是什么？
Local long-term memory plugin for OpenClaw using mem0 + ChromaDB. Gives all agents persistent cross-session semantic memory with auto-recall and auto-capture... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件，目前累计下载 128 次。
如何安装 mem0 Local Memory？
在 OpenClaw 或 Claude Code 对话框中运行命令「/install mem0-local-memory」即可一键安装，无需额外配置。
mem0 Local Memory 是免费的吗？
是的，mem0 Local Memory 完全免费，采用 MIT-0 许可证，可自由下载、安装和使用。
mem0 Local Memory 支持哪些平台？
mem0 Local Memory 跨平台运行，可在任意部署了 OpenClaw / Claude Code 的环境中使用（cross-platform）。
谁开发了 mem0 Local Memory？
由 dream-star-end（@dream-star-end）开发并维护，当前版本 v1.2.0。
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