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mem0-config内存 0 配置

Agent Skill

mem0-config 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

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OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:mem0-config(内存 0 配置)
来源仓库:https://github.com/nyrosveil/mem0-config
安装命令:
openclaw skills install mem0-config
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install mem0-config

简介

mem0-config 用于安装、配置和管理 OpenClaw 中的 mem0 长期记忆插件。

  • 适合希望快速部署和诊断 mem0 功能的用户,简化初始化流程。
  • 提供命令行工具支持配置验证、故障排查与运行时监控。
  • 安装命令为 openclaw skills install mem0-config,建议先阅读文档了解参数设置。
  • 使用前请确认目标环境是否满足 mem0 运行所需的网络与存储条件。

SKILL.md

name
openclaw-mem0
description
Install, configure, diagnose, and operate the openclaw-mem0 long-term memory plugin for OpenClaw agents. Use when the user wants to set up mem0 memory (platform or open-source/self-hosted mode), configure OSS components (embedder, vector store, LLM, historyDbPath), debug memory issues (SQLITE_CANTOPEN crash loops, memories not being stored or recalled, Qdrant/Ollama connectivity), use the openclaw mem0 CLI (search, stats), or understand how auto-recall and auto-capture work in agent sessions.

openclaw-mem0

Long-term memory plugin for OpenClaw agents, powered by Mem0. Extracts and injects memories automatically around each agent turn.

Installation

1. Install the plugin

openclaw plugins install @mem0/openclaw-mem0

This installs the plugin into ~/.openclaw/extensions/openclaw-mem0/ and adds it to openclaw.json.

2. Choose a mode and install dependencies

Platform mode — no local dependencies. Get an API key from app.mem0.ai and skip to Configuration.

Open-source mode — requires two local services:

# Ollama (embedder + LLM)
brew install ollama
ollama serve                        # or: brew services start ollama
ollama pull bge-m3:latest           # embedder (1024-dim)
ollama pull llama3.2                # LLM for memory extraction

# Qdrant (vector store)
docker run -d -p 6333:6333 qdrant/qdrant
# or: brew install qdrant && qdrant

Verify both are running:

curl -s http://localhost:11434/          # → "Ollama is running"
curl -s http://localhost:6333/health     # → {"status":"ok"}

3. Add to openclaw.json

Add under plugins.entries (see Configuration below).

4. Restart the gateway

openclaw gateway stop && openclaw gateway

Confirm the plugin loaded:

grep "openclaw-mem0: initialized" ~/.openclaw/logs/gateway.log | tail -1

Expected output: openclaw-mem0: initialized (mode: open-source, user: ..., autoRecall: true, autoCapture: true)


Modes

ModeConfigRequires
platformapiKey from app.mem0.aiInternet, Mem0 API key
open-sourceoss block (self-hosted)Ollama + Qdrant (or other providers)

Configuration

Minimal Config

Platform:

"openclaw-mem0": {
  "enabled": true,
  "config": { "mode": "platform", "apiKey": "${MEM0_API_KEY}", "userId": "your-id" }
}

Open-source:

"openclaw-mem0": {
  "enabled": true,
  "config": {
    "mode": "open-source",
    "userId": "your-id",
    "oss": {
      "embedder":    { "provider": "ollama", "config": { "model": "bge-m3:latest", "baseURL": "http://localhost:11434" } },
      "vectorStore": { "provider": "qdrant", "config": { "host": "localhost", "port": 6333, "collection": "memories", "dimension": 1024 } },
      "llm":         { "provider": "ollama", "config": { "model": "llama3.2", "baseURL": "http://localhost:11434" } },
      "historyDbPath": "/absolute/path/to/.openclaw/memory/history.db"
    }
  }
}
Always set historyDbPath to an absolute path. When openclaw runs as a LaunchAgent, process.cwd() is /, so the default relative "memory.db" resolves to /memory.db (unwritable on macOS), causing a SQLITE_CANTOPEN crash loop. See troubleshooting.md.

Key Config Options

KeyDefaultNotes
autoRecalltrueInject memories before each agent turn
autoCapturetrueStore memories after each agent turn
topK5Max memories injected per turn
searchThreshold0.5Min similarity score (0–1)
userId"default"Scope memories per user

CLI

openclaw mem0 stats                          # Total memories, mode, user
openclaw mem0 search "user's name"           # Semantic search
openclaw mem0 search "topic" --scope long-term   # long-term | session | all

Agent Tools

The plugin registers 5 tools for agents to call:

ToolDescription
memory_searchSemantic search (scope: session/long-term/all)
memory_listList all memories for a user
memory_storeExplicitly save a fact (longTerm: true by default)
memory_getFetch memory by ID
memory_forgetDelete by ID or query

Verifying It Works

# Check gateway log for injection events
grep "openclaw-mem0: inject" ~/.openclaw/logs/gateway.log | tail -5

# Confirm history DB created at configured path
ls -la /path/to/history.db

# No SQLITE errors since last gateway start
grep "SQLITE_CANTOPEN" ~/.openclaw/logs/gateway.err.log | tail -3

Troubleshooting

See references/troubleshooting.md for:

  • SQLITE_CANTOPEN crash loop (most common issue)
  • Qdrant / Ollama not reachable
  • Memories not being stored or recalled
  • Telegram allowFrom config warning

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

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敏感数据

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安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

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