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OpenClaw Memory Qdrant

OpenClaw 插件 memory-qdrant 提供本地语义记忆能力,通过 Qdrant 向量库(默认内存模式,可选外部服务)与 Transformers.js 本地嵌入(Xenova/all-MiniLM-L6-v2)实现三个工具:memory_store 存储、memory_search 语义检索、memory_forget 删除记忆;无需 API Key,首次运行需联网下载约 25MB…

zuiho-kai
zuiho-kai
热度 91.69
最近更新 2026-05-11 17:25:56
分类:知识依赖:代码执行 / MCP 服务 / 第三方 API应用场景:笔记整理 / 工作流

安装技能

复制下面的话术发给你的 Agent,它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill: npx secure-skills-cli add memory-qdrant
Metadata
name
memory-qdrant
description
Local semantic memory with Qdrant and Transformers.js. Store, search, and recall conversation context using vector embeddings (fully local, no API keys).
version
1.0.10
author
zuiho-kai
homepage
https://github.com/zuiho-kai/openclaw-memory-qdrant
tags
["memory","semantic-search","qdrant","transformers","embeddings","local-ai","vector-db","context"]
metadata
{"openclaw":{"requires":{"bins":["node","npm"]}}}

memory-qdrant

Use when you need your OpenClaw agent to remember and recall information across conversations using semantic search.

Local semantic memory plugin powered by Qdrant vector database and Transformers.js embeddings. Zero configuration, fully local, no API keys required.

Features

  • Semantic search with local Transformers.js embeddings
  • In-memory mode (zero config) or persistent Qdrant storage
  • Optional auto-capture of conversation context (opt-in, disabled by default)
  • Context-aware memory recall
  • Fully local, no API keys or external services required

Installation

clawhub install memory-qdrant

First-time setup: This plugin downloads a 25MB embedding model from Hugging Face on first run and may require build tools for native dependencies (sharp, onnxruntime). See README for detailed installation requirements.

Configuration

Enable in your OpenClaw config:

{
  "plugins": {
    "memory-qdrant": {
      "enabled": true
    }
  }
}

Options:

  • autoCapture (default: false) - Auto-record conversations. Note: trigger patterns include email/phone regex, so enabling this may capture PII.
  • autoRecall (default: true) - Auto-inject relevant memories
  • qdrantUrl (optional) - External Qdrant server (leave empty for in-memory)

Usage

Three tools available:

memory_store - Save information

memory_store({
  text: "User prefers Opus for complex tasks",
  category: "preference"
})

memory_search - Find relevant memories

memory_search({
  query: "workflow preferences",
  limit: 5
})

memory_forget - Delete memories

memory_forget({ memoryId: "uuid" })
// or
memory_forget({ query: "text to forget" })

Privacy & Security

  • In-memory mode (default): Data cleared on restart
  • Qdrant mode: Data sent to configured server (use trusted servers only)
  • Network: Downloads ~25MB model from Hugging Face on first run
  • autoCapture: Disabled by default for privacy. Trigger patterns match emails and phone-like numbers, so enabling autoCapture can capture PII.

Technical Details

  • Vector DB: Qdrant (in-memory or external)
  • Embeddings: Xenova/all-MiniLM-L6-v2 (local)
  • Module: ES6 with factory function pattern

Links