OpenClaw Memory System

让 OpenClaw 真的记住用户偏好、事实和上下文的长期记忆 skill。适用于你受不了每次新会话都要重复背景、希望 agent 能跨会话记住信息、并且想直接拥有可搜索、可持久化、可自动注入的记忆系统时使用。不是手工记笔记，而是一个已经做好的可运行记忆能力。

让 OpenClaw 跨会话真的记住你的偏好、事实和上下文。

一句话卖点

不是再重复背景、重复偏好、重复项目上下文，而是直接给你的 agent 装上一套可持久化、可搜索、可自动取回的长期记忆系统。

What is it?

这是一个已经做好的长期记忆 skill：

• 记住用户偏好
• 记住项目背景
• 记住反复提过的事实
• 下次会话可直接搜索和取回

你装上的不是“怎么做记忆系统的教程”，而是一套可运行的记忆能力。

为什么值得装

很多人真正烦的不是 agent 不够聪明，而是：

• 每次开新会话都像失忆
• 一遍遍重复偏好和背景
• 项目上下文丢了还要重新讲
• 明明说过的话，下次又得重来

这个 skill 解决的是：

把“记忆”从手工补上下文，变成 agent 自己能持续用的底层能力。

Key Features

• 🧠 Persistent Memory - Remembers everything across sessions
• 🔍 Semantic Search - Find memories by meaning, not just keywords
• 🤖 Automatic Learning - Extracts facts and preferences automatically
• 💾 Local Storage - SQLite database with vector embeddings
• 💰 x402 Payments - Agents can pay for unlimited storage (0.5 USDT/month)

Free vs Pro Tier

Free Tier:

• 100 memories maximum
• 7-day retention
• Basic semantic search

Pro Tier (0.5 USDT/month):

• Unlimited memories
• Permanent retention
• Advanced semantic search
• Memory relationship mapping

Installation

claw skill install openclaw-memory

Commands

# Search memories
claw memory search "What does user prefer?"

# List recent memories
claw memory list --limit=10

# Show stats
claw memory stats

# Open dashboard
claw memory dashboard

# Subscribe to Pro
claw memory subscribe

How It Works

1. Hooks into requests - Automatically extracts important information
2. Generates embeddings - Creates semantic vectors for search
3. Stores locally - SQLite database with full privacy
4. Retrieves on demand - Injects relevant memories before requests
5. Manages quota - Prunes old memories when limits reached (Free tier)

Use Cases

• Remember user preferences and coding style
• Store project context and requirements
• Learn patterns from repeated interactions
• Maintain conversation history across sessions
• Build knowledge base over time

Agent Economy

Agents can autonomously evaluate if Pro tier is worth it:

• Cost: 0.5 USDT/month
• Value: Saves tokens by eliminating context repetition
• ROI: If persistent memory saves >0.5 USDT/month in tokens, it pays for itself

See AGENT-PAYMENTS.md for x402 integration details.

Privacy

• All data stored locally in ~/.openclaw/openclaw-memory/
• No external servers or telemetry
• Embeddings can use local models (no API calls)
• Open source - audit the code yourself

Dashboard

Access web UI at http://localhost:9091:

• Browse and search memories
• View memory timeline
• Check quota and stats
• Manage Pro subscription

Foundation for Future Tools

Memory System is the foundation for:

• Context Optimizer - Uses memories to compress context
• Smart Router - Learns routing patterns
• Rate Limit Manager - Tracks usage patterns

Requirements

• Node.js 18+
• OpenClaw v2026.1.30+
• OS: Windows, macOS, Linux

Links

• Documentation
• Agent Payments Guide
• GitHub Repository
• ClawHub Page

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Built by the OpenClaw community | First memory system with x402 payments