Google Vertex AI Memory Bank

v1.0.0

Install and configure the OpenClaw Vertex AI Memory Bank plugin for persistent, cross-agent memory. Use when the user wants long-term memory, cross-session r...

0· 267· 1 versions· 0 current· 0 all-time· Updated 22h ago· MIT-0
byShubham Saboo@shubhamsaboo

Install

openclaw skills install vertexai-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:

  • 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 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

OptionDefaultDescription
projectIdrequiredGCP project ID or number
locationrequiredGCP region (e.g. us-central1)
reasoningEngineIdrequiredAgent Engine reasoning engine ID
autoRecalltrueRetrieve memories before each turn
autoCapturetrueStore memories after each turn
autoSyncFilestrueSync workspace .md files to Memory Bank
autoSyncTopicstrueAuto-configure memory topics at startup
topK10Max memories to retrieve per query
perspective"third"Memory perspective (first or third person)
backgroundGeneratetrueFire-and-forget memory generation
ttlSecondsnoneAuto-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:

  • [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

Version tags

latestvk97dnkc9zc3bkbz9bgfwk11s0h831vz7