openclaw-redis-agent-memory

Long-term memory plugin for OpenClaw using Redis vector search.

Give your AI agent persistent memory across conversations - it can remember user preferences, past decisions, important facts, and more.

Features

• Auto-recall: Automatically inject relevant memories into context before each turn
• Auto-capture: Save conversations to working memory for background extraction
• Manual tools: memory_recall, memory_store, memory_forget for explicit control
• Summary Views: Rolling summaries of long-term memories for stable context
• Multi-tenancy: Namespace and userId support for memory isolation
• Configurable tool descriptions: Customize how the LLM sees and uses memory tools

Quick Start

1. Start the Memory Server

The easiest way to run the memory server is with the standalone Docker image (includes Redis):

# Create .env file with your OpenAI key
echo "OPENAI_API_KEY=sk-your-key-here" > .env

# Run the standalone image
docker run -d \
  --name agent-memory \
  --platform linux/amd64 \
  --env-file .env \
  -p 8000:8000 \
  redislabs/agent-memory-server:0.13.1-standalone

For more configuration options, see the agent-memory-server documentation.

2. Install the Plugin

openclaw plugins install openclaw-redis-agent-memory

3. Configure OpenClaw

Edit ~/.openclaw/openclaw.json:

{
  "plugins": {
    "entries": {
      "redis-memory": {
        "enabled": true,
        "config": {
          "serverUrl": "http://localhost:8000",
          "namespace": "my-app",
          "userId": "user-123"
        }
      }
    }
  }
}

Configuration Options

| Option | Type | Default | Description | |--------|------|---------|-------------| | serverUrl | string | http://localhost:8000 | Base URL of agent-memory-server | | apiKey | string | - | API key for authentication | | bearerToken | string | - | Bearer token for authentication | | namespace | string | default | Namespace for memory isolation | | userId | string | default | User ID for memory isolation | | timeout | number | 30000 | Request timeout in milliseconds | | autoCapture | boolean | true | Auto-save conversations for extraction | | autoRecall | boolean | true | Auto-inject relevant memories | | minScore | number | 0.3 | Minimum similarity score (0-1) | | recallLimit | number | 3 | Max memories to recall | | extractionStrategy | string | discrete | discrete, summary, preferences, or custom | | customPrompt | string | - | Custom extraction prompt (for custom strategy) | | summaryViewName | string | agent_user_summary | Name for the summary view | | summaryTimeWindowDays | number | 30 | Rolling window for summaries | | summaryGroupBy | array | ["user_id"] | Fields to partition summaries | | recallDescription | string | - | Custom description for memory_recall tool | | storeDescription | string | - | Custom description for memory_store tool | | forgetDescription | string | - | Custom description for memory_forget tool |

Tools

memory_recall

Search through long-term memories.

{
  "query": "user preferences for notifications",
  "limit": 5
}

memory_store

Save important information to long-term memory.

{
  "text": "User prefers dark mode",
  "category": "preference"
}

Categories: preference, fact, decision, entity, other

memory_forget

Delete specific memories (GDPR-compliant).

{
  "query": "dark mode preference"
}

Or by ID:

{
  "memoryId": "abc123"
}

Extraction Strategies

• discrete (default): Extract semantic and episodic memories
• summary: Maintain a running conversation summary
• preferences: Focus on user preferences and settings
• custom: Use your own extraction prompt

Environment Variables

Use ${VAR_NAME} syntax for environment variable substitution:

{
  "serverUrl": "${AGENT_MEMORY_SERVER_URL}",
  "apiKey": "${AGENT_MEMORY_API_KEY}"
}

Server Configuration

The .env file for agent-memory-server supports many options:

# Required
OPENAI_API_KEY=sk-your-key-here

# Optional - customize the embedding model
# OPENAI_EMBEDDING_MODEL=text-embedding-3-small

# Optional - use a different LLM for memory extraction
# OPENAI_LLM_MODEL=gpt-4o-mini

See the full configuration reference for all options.

Programmatic Usage

import redisMemoryPlugin, { memoryConfigSchema } from "openclaw-redis-agent-memory";

// Parse config
const config = memoryConfigSchema.parse({
  serverUrl: "http://localhost:8000",
  namespace: "my-app",
});

// Register with your plugin system
redisMemoryPlugin.register(yourPluginApi);

Links

• agent-memory-server documentation
• OpenClaw

License

MIT