OpenClaw plugin for long-term AI agent memory using Redis vector search
npm install 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.
- 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
The easiest way to run the memory server is with the standalone Docker image (includes Redis):
``bashCreate .env file with your OpenAI key
echo "OPENAI_API_KEY=sk-your-key-here" > .env
For more configuration options, see the agent-memory-server documentation.
$3
bash
openclaw plugins install openclaw-redis-agent-memory
`$3
Edit
:`json
{
"plugins": {
"entries": {
"redis-memory": {
"enabled": true,
"config": {
"serverUrl": "http://localhost:8000",
"namespace": "my-app",
"userId": "user-123"
}
}
}
}
}
`Configuration Options
| Option | Type | Default | Description |
|--------|------|---------|-------------|
|
| 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
$3
Search through long-term memories.
`json
{
"query": "user preferences for notifications",
"limit": 5
}
`$3
Save important information to long-term memory.
json
{
"text": "User prefers dark mode",
"category": "preference"
}
`Categories:
, fact, decision, entity, other$3
Delete specific memories (GDPR-compliant).
json
{
"query": "dark mode preference"
}
`Or by ID:
json
{
"memoryId": "abc123"
}
`Extraction Strategies
- discrete (default): Extract semantic and episodic memories
- summary: Maintain a running conversation summary
- preferences: Focus on user preferences and settings
- custom: Use your own extraction prompt
Environment Variables
Use
syntax for environment variable substitution:`json
{
"serverUrl": "${AGENT_MEMORY_SERVER_URL}",
"apiKey": "${AGENT_MEMORY_API_KEY}"
}
`Server Configuration
The
file for agent-memory-server supports many options:`bash
Required
OPENAI_API_KEY=sk-your-key-hereOptional - 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
typescript
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);
``- agent-memory-server documentation
- OpenClaw
MIT