Google Vertex AI Memory Bank

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:

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 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

# 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

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

Step 3: Configure openclaw.json

Add to your openclaw.json under plugins:

{
  "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

openclaw gateway restart

Configuration Options

| Option | Default | Description | |--------|---------|-------------| | projectId | required | GCP project ID or number | | location | required | GCP region (e.g. us-central1) | | reasoningEngineId | required | Agent Engine reasoning engine ID | | autoRecall | true | Retrieve memories before each turn | | autoCapture | true | Store memories after each turn | | autoSyncFiles | true | Sync workspace .md files to Memory Bank | | autoSyncTopics | true | Auto-configure memory topics at startup | | topK | 10 | Max memories to retrieve per query | | perspective | "third" | Memory perspective (first or third person) | | backgroundGenerate | true | Fire-and-forget memory generation | | ttlSeconds | none | Auto-expire memories after N seconds |

Verifying It Works

After installation, check the gateway log:

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

You should see:

CLI Commands

The plugin adds these commands:

Troubleshooting

Source

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

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.