Vertex AI Memory Bank Plugin#

Give your OpenClaw agent persistent, cross-agent memory powered by Google's Vertex AI Memory Bank.

What This Does#

After setup, your agent will:

• Auto-recall: Before each turn, relevant memories are retrieved and injected into context
• Auto-capture: After each turn, facts are extracted and stored automatically
• File sync: Workspace files (MEMORY.md, USER.md, SOUL.md) sync to Memory Bank with hash tracking
• Cross-agent: Tell one agent something, all agents remember it

Prerequisites#

Before running the setup script, ensure:

1. Google Cloud SDK installed and authenticated ( gcloud auth application-default login)
2. A GCP project with billing enabled
3. Vertex AI API enabled on the project
4. Node.js 18+ and npm installed

If the user doesn't have these, help them set up each one.

Installation#

Run the setup script:

bash

bash scripts/setup.sh

This script will:

1. Check for required tools (gcloud, npm, node)
2. Prompt for GCP project ID and region
3. Create a Vertex AI Agent Engine reasoning engine (Memory Bank instance)
4. Install the npm plugin package
5. Add the plugin configuration to openclaw.json
6. Restart the gateway to load the plugin

Manual Installation#

If the script doesn't work for your environment, follow these steps:

Step 1: Create a Memory Bank Instance#

bash

# Set your project
gcloud config set project YOUR_PROJECT_ID

# Create a reasoning engine for Memory Bank
curl -X POST \
  "https://REGION-aiplatform.googleapis.com/v1beta1/projects/YOUR_PROJECT_ID/locations/REGION/reasoningEngines" \
  -H "Authorization: Bearer $(gcloud auth print-access-token)" \
  -H "Content-Type: application/json" \
  -d '{"display_name": "openclaw-memory-bank"}'

Note the reasoning engine ID from the response.

Step 2: Install the Plugin#

bash

cd /path/to/openclaw-vertex-memorybank
npm install
npm run build

Step 3: Configure openclaw.json#

Add to your openclaw.json under plugins:

json

{
  "plugins": {
    "openclaw-vertex-memorybank": {
      "enabled": true,
      "path": "/path/to/openclaw-vertex-memorybank",
      "config": {
        "projectId": "YOUR_PROJECT_ID",
        "location": "us-central1",
        "reasoningEngineId": "YOUR_REASONING_ENGINE_ID"
      }
    }
  }
}

Step 4: Restart#

bash

openclaw gateway restart

Configuration Options#

OptionDefaultDescriptionprojectIdrequiredGCP project ID or numberlocationrequiredGCP region (e.g. us-central1)reasoningEngineIdrequiredAgent Engine reasoning engine IDautoRecalltrueRetrieve memories before each turnautoCapturetrueStore memories after each turnautoSyncFilestrueSync workspace .md files to Memory BankautoSyncTopicstrueAuto-configure memory topics at startuptopK10Max memories to retrieve per queryperspective"third"Memory perspective (first or third person)backgroundGeneratetrueFire-and-forget memory generationttlSecondsnoneAuto-expire memories after N seconds

Verifying It Works#

After installation, check the gateway log:

bash

tail -f ~/.openclaw/logs/gateway.log | grep memory

You should see:

• [memory-vertex] synced N topics on startup
• [memory-vertex] recall: N memories on each turn
• [memory-vertex] capture fired (bg) after each turn

CLI Commands#

The plugin adds these commands:

• memorybank-search <query> - Search your memories
• memorybank-remember <fact> - Store a specific fact
• memorybank-forget <memory_id> - Delete a memory
• memorybank-sync - Force sync workspace files
• memorybank-status - Check plugin status
• memorybank-list - List all stored memories

Troubleshooting#

• "401 Unauthorized": Run gcloud auth application-default login
• "Memory Bank not found": Check reasoningEngineId matches your instance
• No memories recalled: Check topK and maxDistance settings. Try memorybank-search to verify memories exist
• High token usage: Reduce topK or set introspection: "off" to remove similarity scores

Source#

Full source code and documentation: https://github.com/Shubhamsaboo/openclaw-vertexai-memorybank