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Google AI profile image Gleb Otochkin
Gleb Otochkin for Google AI

Posted on • Originally published at codelabs.developers.google.com

AlloyDB Agentic RAG Application with MCP Toolbox [Part 1]

#database #agents #mcp #ai

1. Introduction

In this codelab, you will learn how to create an AlloyDB cluster, deploy the MCP toolbox, and configure it to use AlloyDB as a data source. You'll then build a sample interactive RAG application that uses the deployed toolbox to ground its requests.

You can get more information about the MCP Toolbox on the documentation page and the sample Cymbal Air application here.

This lab is part of a lab collection dedicated to AlloyDB AI features. You can read more on the AlloyDB AI page in documentation and see other labs.

Prerequisites

  • A basic understanding of the Google Cloud Console
  • Basic skills in command line interface and Google Cloud shell

What you'll learn

✅ How to deploy AlloyDB Cluster with Vertex AI integration
✅ How to connect to the AlloyDB
✅ How to configure and deploy MCP Tooolbox Service
✅ How to deploy a sample application using the deployed service

What you'll need

  • A Google Cloud Account and Google Cloud Project
  • A web browser such as Chrome

2. Setup and Requirements

Self-paced environment setup

  1. Sign-in to the Google Cloud Console and create a new project or reuse an existing one. If you don't already have a Gmail or Google Workspace account, you must create one.
  • The Project name is the display name for this project's participants. It is a character string not used by Google APIs. You can always update it.
  • The Project ID is unique across all Google Cloud projects and is immutable (cannot be changed after it has been set). The Cloud Console auto-generates a unique string; usually you don't care what it is. In most codelabs, you'll need to reference your Project ID (typically identified as PROJECT_ID). If you don't like the generated ID, you might generate another random one. Alternatively, you can try your own, and see if it's available. It can't be changed after this step and remains for the duration of the project.
  • For your information, there is a third value, a Project Number, which some APIs use. Learn more about all three of these values in the documentation.

⚠️ Caution: A project ID is globally unique and can't be used by anyone else after you've selected it. You are the only user of that ID. Even if a project is deleted, the ID can't be used again

📝 Note: If you use a Gmail account, you can leave the default location set to No organization. If you use a Google Workspace

  1. Next, you'll need to enable billing in the Cloud Console to use Cloud resources/APIs. Running through this codelab won't cost much, if anything at all. To shut down resources to avoid incurring billing beyond this tutorial, you can delete the resources you created or delete the project. New Google Cloud users are eligible for the $300 USD Free Trial program.

Start Cloud Shell

While Google Cloud can be operated remotely from your laptop, in this codelab you will be using Google Cloud Shell, a command line environment running in the Cloud.

From the Google Cloud Console, click the Cloud Shell icon on the top right toolbar:

Activate the Cloud Shell

It should only take a few moments to provision and connect to the environment. When it is finished, you should see something like this:

Screenshot of Google Cloud Shell terminal showing that the environment has connected

This virtual machine is loaded with all the development tools you'll need. It offers a persistent 5GB home directory, and runs on Google Cloud, greatly enhancing network performance and authentication. All of your work in this codelab can be done within a browser. You do not need to install anything.

3. Before you begin

Enable API

Output:

Please be aware that some resources you enable are going to incur some cost if you are not using the promotional tier. In normal circumstances if all the resources are destroyed upon completion of the lab the cost of all resources would not exceed $5. We recommend checking your billing and making sure the exercise is acceptable for you.

Inside Cloud Shell, make sure that your project ID is setup:

Usually the project ID is shown in parentheses in the command prompt in the cloud shell as it is shown in the picture:


gcloud config set project [YOUR-PROJECT-ID]
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Then set the PROJECT_ID environment variable to your Google Cloud project ID:

PROJECT_ID=$(gcloud config get-value project)
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Enable all necessary services:

gcloud services enable alloydb.googleapis.com \
                       compute.googleapis.com \
                       cloudresourcemanager.googleapis.com \
                       servicenetworking.googleapis.com \
                       vpcaccess.googleapis.com \
                       aiplatform.googleapis.com \
                       cloudbuild.googleapis.com \
                       artifactregistry.googleapis.com \
                       run.googleapis.com \
                       iam.googleapis.com \
                       secretmanager.googleapis.com
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Expected output

student@cloudshell:~ (gleb-test-short-004)$ gcloud services enable alloydb.googleapis.com \
                       compute.googleapis.com \
                       cloudresourcemanager.googleapis.com \
                       servicenetworking.googleapis.com \
                       vpcaccess.googleapis.com \
                       aiplatform.googleapis.com \
                       cloudbuild.googleapis.com \
                       artifactregistry.googleapis.com \
                       run.googleapis.com \
                       iam.googleapis.com \
                       secretmanager.googleapis.com
Operation "operations/acf.p2-404051529011-664c71ad-cb2b-4ab4-86c1-1f3157d70ba1" finished successfully.
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4. Deploy AlloyDB Cluster

Create AlloyDB cluster and primary instance. The following procedure describes how to create an AlloyDB cluster and instance using Google Cloud SDK. If you prefer the console approach you can follow the documentation here.

Before creating an AlloyDB cluster we need an available private IP range in our VPC to be used by the future AlloyDB instance. If we don't have it then we need to create it, assign it to be used by internal Google services and after that we will be able to create the cluster and instance.

Create private IP range

📝 Note: This step is required only if you don't already have an unused private IP range assigned to work with Google internal services.

We need to configure Private Service Access configuration in our VPC for AlloyDB. The assumption here is that we have the "default" VPC network in the project and it is going to be used for all actions.

Create the private IP range:

gcloud compute addresses create psa-range \
    --global \
    --purpose=VPC_PEERING \
    --prefix-length=24 \
    --description="VPC private service access" \
    --network=default
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Create private connection using the allocated IP range:

gcloud services vpc-peerings connect \
    --service=servicenetworking.googleapis.com \
    --ranges=psa-range \
    --network=default
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📝 Note: The second command takes a couple of minutes to execute

Expected console output:

student@cloudshell:~ (test-project-402417)$ gcloud compute addresses create psa-range \
    --global \
    --purpose=VPC_PEERING \
    --prefix-length=24 \
    --description="VPC private service access" \
    --network=default
Created [https://www.googleapis.com/compute/v1/projects/test-project-402417/global/addresses/psa-range].

student@cloudshell:~ (test-project-402417)$ gcloud services vpc-peerings connect \
    --service=servicenetworking.googleapis.com \
    --ranges=psa-range \
    --network=default
Operation "operations/pssn.p24-4470404856-595e209f-19b7-4669-8a71-cbd45de8ba66" finished successfully.

student@cloudshell:~ (test-project-402417)$
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Create AlloyDB Cluster

In this section we are creating an AlloyDB cluster in the us-central1 region.

Define password for the postgres user. You can define your own password or use a random function to generate one

export PGPASSWORD=`openssl rand -hex 12`
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Expected console output:

student@cloudshell:~ (test-project-402417)$ export PGPASSWORD=`openssl rand -hex 12`
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Note the PostgreSQL password for future use.

echo $PGPASSWORD
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You will need that password in the future to connect to the instance as the postgres user. I suggest writing it down or copying it somewhere to be able to use later.

Expected console output:

student@cloudshell:~ (test-project-402417)$ echo $PGPASSWORD
bbefbfde7601985b0dee5723
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Create a Free Trial Cluster

If you haven't been using AlloyDB before you can create a free trial cluster:

Define region and AlloyDB cluster name. We are going to use us-central1 region and alloydb-aip-01 as a cluster name:

export REGION=us-central1
export ADBCLUSTER=alloydb-aip-01
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Run command to create the cluster:

gcloud alloydb clusters create $ADBCLUSTER \
    --password=$PGPASSWORD \
    --network=default \
    --region=$REGION \
    --subscription-type=TRIAL
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Expected console output:

export REGION=us-central1
export ADBCLUSTER=alloydb-aip-01
gcloud alloydb clusters create $ADBCLUSTER \
    --password=$PGPASSWORD \
    --network=default \
    --region=$REGION \
    --subscription-type=TRIAL
Operation ID: operation-1697655441138-6080235852277-9e7f04f5-2012fce4
Creating cluster...done.
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Create an AlloyDB primary instance for our cluster in the same cloud shell session. If you are disconnected you will need to define the region and cluster name environment variables again.

📝 Note: The instance creation usually takes 6-10 minutes to complete

gcloud alloydb instances create $ADBCLUSTER-pr \
    --instance-type=PRIMARY \
    --cpu-count=8 \
    --region=$REGION \
    --cluster=$ADBCLUSTER
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Expected console output:

student@cloudshell:~ (test-project-402417)$ gcloud alloydb instances create $ADBCLUSTER-pr \
    --instance-type=PRIMARY \
    --cpu-count=8 \
    --region=$REGION \
    --availability-type ZONAL \
    --cluster=$ADBCLUSTER
Operation ID: operation-1697659203545-6080315c6e8ee-391805db-25852721
Creating instance...done.
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Create AlloyDB Standard Cluster

If it is not your first AlloyDB cluster in the project proceed with creation of a standard cluster.

Define region and AlloyDB cluster name. We are going to use us-central1 region and alloydb-aip-01 as a cluster name:

export REGION=us-central1
export ADBCLUSTER=alloydb-aip-01
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Run command to create the cluster:

gcloud alloydb clusters create $ADBCLUSTER \
    --password=$PGPASSWORD \
    --network=default \
    --region=$REGION
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Expected console output:

export REGION=us-central1
export ADBCLUSTER=alloydb-aip-01
gcloud alloydb clusters create $ADBCLUSTER \
    --password=$PGPASSWORD \
    --network=default \
    --region=$REGION 
Operation ID: operation-1697655441138-6080235852277-9e7f04f5-2012fce4
Creating cluster...done.
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Create an AlloyDB primary instance for our cluster in the same cloud shell session. If you are disconnected you will need to define the region and cluster name environment variables again.

📝 Note: The instance creation usually takes 6-10 minutes to complete

gcloud alloydb instances create $ADBCLUSTER-pr \
    --instance-type=PRIMARY \
    --cpu-count=2 \
    --region=$REGION \
    --cluster=$ADBCLUSTER
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Expected console output:

student@cloudshell:~ (test-project-402417)$ gcloud alloydb instances create $ADBCLUSTER-pr \
    --instance-type=PRIMARY \
    --cpu-count=2 \
    --region=$REGION \
    --availability-type ZONAL \
    --cluster=$ADBCLUSTER
Operation ID: operation-1697659203545-6080315c6e8ee-391805db-25852721
Creating instance...done.
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Grant Necessary Permissions to AlloyDB

Add Vertex AI permissions to the AlloyDB service agent.

Open another Cloud Shell tab using the sign "+" at the top.

In the new cloud shell tab execute:

PROJECT_ID=$(gcloud config get-value project)
gcloud projects add-iam-policy-binding $PROJECT_ID \
  --member="serviceAccount:service-$(gcloud projects describe $PROJECT_ID --format="value(projectNumber)")@gcp-sa-alloydb.iam.gserviceaccount.com" \
  --role="roles/aiplatform.user"
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Expected console output:

student@cloudshell:~ (test-project-001-402417)$ PROJECT_ID=$(gcloud config get-value project)
Your active configuration is: [cloudshell-11039]
student@cloudshell:~ (test-project-001-402417)$ gcloud projects add-iam-policy-binding $PROJECT_ID \
  --member="serviceAccount:service-$(gcloud projects describe $PROJECT_ID --format="value(projectNumber)")@gcp-sa-alloydb.iam.gserviceaccount.com" \
  --role="roles/aiplatform.user"
Updated IAM policy for project [test-project-001-402417].
bindings:
- members:
  - serviceAccount:service-4470404856@gcp-sa-alloydb.iam.gserviceaccount.com
  role: roles/aiplatform.user
- members:
...
etag: BwYIEbe_Z3U=
version: 1
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Close the tab by either execution command "exit" in the tab:

exit
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5. Prepare GCE Virtual Machine

We are going to use a Google Compute Engine (GCE) VM as our platform to work with the database and deploy different parts of the sample application. Using a VM gives us more flexibility in installed components and direct access to the private AlloyDB IP for data preparation steps.

Create Service Account

Since we will use our VM to deploy the MCP Toolbox as a service and deploy or host the sample application, the first step is to create a Google Service Account (GSA). The GSA will be used by the GCE VM, and we will need to grant it the necessary privileges to work with other services.

In the Cloud Shell execute:

PROJECT_ID=$(gcloud config get-value project)
gcloud iam service-accounts create compute-aip --project $PROJECT_ID

gcloud projects add-iam-policy-binding $PROJECT_ID \
  --member="serviceAccount:compute-aip@$PROJECT_ID.iam.gserviceaccount.com" \
  --role="roles/cloudbuild.builds.editor"

gcloud projects add-iam-policy-binding $PROJECT_ID \
  --member="serviceAccount:compute-aip@$PROJECT_ID.iam.gserviceaccount.com" \
  --role="roles/artifactregistry.admin"

gcloud projects add-iam-policy-binding $PROJECT_ID \
  --member="serviceAccount:compute-aip@$PROJECT_ID.iam.gserviceaccount.com" \
  --role="roles/storage.admin"

gcloud projects add-iam-policy-binding $PROJECT_ID \
  --member="serviceAccount:compute-aip@$PROJECT_ID.iam.gserviceaccount.com" \
  --role="roles/run.admin"

gcloud projects add-iam-policy-binding $PROJECT_ID \
  --member="serviceAccount:compute-aip@$PROJECT_ID.iam.gserviceaccount.com" \
  --role="roles/iam.serviceAccountUser"

gcloud projects add-iam-policy-binding $PROJECT_ID \
  --member="serviceAccount:compute-aip@$PROJECT_ID.iam.gserviceaccount.com" \
  --role="roles/alloydb.viewer"

gcloud projects add-iam-policy-binding $PROJECT_ID \
  --member="serviceAccount:compute-aip@$PROJECT_ID.iam.gserviceaccount.com" \
  --role="roles/alloydb.client"

gcloud projects add-iam-policy-binding $PROJECT_ID \
  --member="serviceAccount:compute-aip@$PROJECT_ID.iam.gserviceaccount.com" \
  --role="roles/aiplatform.user"

gcloud projects add-iam-policy-binding $PROJECT_ID \
  --member="serviceAccount:compute-aip@$PROJECT_ID.iam.gserviceaccount.com" \
  --role="roles/serviceusage.serviceUsageConsumer"

gcloud projects add-iam-policy-binding $PROJECT_ID \
    --member serviceAccount:compute-aip@$PROJECT_ID.iam.gserviceaccount.com \
    --role roles/secretmanager.admin
Deploy GCE VM
Create a GCE VM in the same region and VPC as the AlloyDB cluster.
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In Cloud Shell execute:

ZONE=us-central1-a
PROJECT_ID=$(gcloud config get-value project)
gcloud compute instances create instance-1 \
    --zone=$ZONE \
    --create-disk=auto-delete=yes,boot=yes,image=projects/debian-cloud/global/images/$(gcloud compute images list --filter="family=debian-12 AND family!=debian-12-arm64" --format="value(name)") \
    --scopes=https://www.googleapis.com/auth/cloud-platform \
    --service-account=compute-aip@$PROJECT_ID.iam.gserviceaccount.com
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Expected console output:

student@cloudshell:~ (test-project-402417)$ ZONE=us-central1-a
PROJECT_ID=$(gcloud config get-value project)
gcloud compute instances create instance-1 \
    --zone=$ZONE \
    --create-disk=auto-delete=yes,boot=yes,image=projects/debian-cloud/global/images/$(gcloud compute images list --filter="family=debian-12 AND family!=debian-12-arm64" --format="value(name)") \
    --scopes=https://www.googleapis.com/auth/cloud-platform \
    --service-account=compute-aip@$PROJECT_ID.iam.gserviceaccount.com
Your active configuration is: [cloudshell-10282]
Created [https://www.googleapis.com/compute/v1/projects/gleb-test-short-002-470613/zones/us-central1-a/instances/instance-1].
NAME: instance-1
ZONE: us-central1-a
MACHINE_TYPE: n1-standard-1
PREEMPTIBLE: 
INTERNAL_IP: 10.128.0.2
EXTERNAL_IP: 34.28.55.32
STATUS: RUNNING
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Install Postgres Client

Install the PostgreSQL client software on the deployed VM

Connect to the VM:

🗒️ Note: First time the SSH connection to the VM can take longer since the process includes creation of RSA key for secure connection and propagating the public part of the key to the project

gcloud compute ssh instance-1 --zone=us-central1-a
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Expected console output:

student@cloudshell:~ (test-project-402417)$ gcloud compute ssh instance-1 --zone=us-central1-a
Updating project ssh metadata...working..Updated [https://www.googleapis.com/compute/v1/projects/test-project-402417].                                                                                                                                                         
Updating project ssh metadata...done.                                                                                                                                                                                                                                              
Waiting for SSH key to propagate.
Warning: Permanently added 'compute.5110295539541121102' (ECDSA) to the list of known hosts.
Linux instance-1 5.10.0-26-cloud-amd64 #1 SMP Debian 5.10.197-1 (2023-09-29) x86_64

The programs included with the Debian GNU/Linux system are free software;
the exact distribution terms for each program are described in the
individual files in /usr/share/doc/*/copyright.

Debian GNU/Linux comes with ABSOLUTELY NO WARRANTY, to the extent
permitted by applicable law.
student@instance-1:~$
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Install the software running command inside the VM:

sudo apt-get update
sudo apt-get install --yes postgresql-client
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Expected console output:

student@instance-1:~$ sudo apt-get update
sudo apt-get install --yes postgresql-client
Get:1 file:/etc/apt/mirrors/debian.list Mirrorlist [30 B]
Get:4 file:/etc/apt/mirrors/debian-security.list Mirrorlist [39 B]
Hit:7 https://packages.cloud.google.com/apt google-compute-engine-bookworm-stable InRelease
Get:8 https://packages.cloud.google.com/apt cloud-sdk-bookworm InRelease [1652 B]
Get:2 https://deb.debian.org/debian bookworm InRelease [151 kB]
Get:3 https://deb.debian.org/debian bookworm-updates InRelease [55.4 kB]
...redacted...
update-alternatives: using /usr/share/postgresql/15/man/man1/psql.1.gz to provide /usr/share/man/man1/psql.1.gz (psql.1.gz) in auto mode
Setting up postgresql-client (15+248) ...
Processing triggers for man-db (2.11.2-2) ...
Processing triggers for libc-bin (2.36-9+deb12u7) ...
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Connect to the AlloyDB Instance

Connect to the primary instance from the VM using psql.

Continue with the opened SSH session to your VM. If you have been disconnected then connect again using the same command as above.

Use the previously noted $PGASSWORD and the cluster name to connect to AlloyDB from the GCE VM:

export PGPASSWORD=<Noted password>
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PROJECT_ID=$(gcloud config get-value project)
REGION=us-central1
ADBCLUSTER=alloydb-aip-01
INSTANCE_IP=$(gcloud alloydb instances describe $ADBCLUSTER-pr --cluster=$ADBCLUSTER --region=$REGION --format="value(ipAddress)")
psql "host=$INSTANCE_IP user=postgres sslmode=require"
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Expected console output:

student@instance-1:~$ PROJECT_ID=$(gcloud config get-value project)
REGION=us-central1
ADBCLUSTER=alloydb-aip-01
INSTANCE_IP=$(gcloud alloydb instances describe $ADBCLUSTER-pr --cluster=$ADBCLUSTER --region=$REGION --format="value(ipAddress)")
psql "host=$INSTANCE_IP user=postgres sslmode=require"
psql (15.13 (Debian 15.13-0+deb12u1), server 16.8)
WARNING: psql major version 15, server major version 16.
         Some psql features might not work.
SSL connection (protocol: TLSv1.3, cipher: TLS_AES_256_GCM_SHA384, compression: off)
Type "help" for help.

postgres=>
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Exit from the psql session keeping the SSH connection up:

exit
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Expected console output:

postgres=> exit
student@instance-1:~$
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6. Initialize the database

We are going to use our client VM as a platform to populate our database with data and host our application. The first step is to create a database and populate it with data.

Create Database

Create a database with the name "assistantdemo".

In the GCE VM session execute:

📝 Note: If your SSH session was terminated you need to reset your environment variables such as:

export PGPASSWORD=

export REGION=us-central1

export ADBCLUSTER=alloydb-aip-01

export INSTANCE_IP=$(gcloud alloydb instances describe $ADBCLUSTER-pr --cluster=$ADBCLUSTER --region=$REGION --format="value(ipAddress)")

psql "host=$INSTANCE_IP user=postgres" -c "CREATE DATABASE assistantdemo"
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Expected console output:

student@instance-1:~$ psql "host=$INSTANCE_IP user=postgres" -c "CREATE DATABASE assistantdemo"
CREATE DATABASE
student@instance-1:~$
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Prepare Python Environment

To continue we are going to use prepared Python scripts from GitHub repository but before doing that we need to install the required software.

In the GCE VM execute:

sudo apt install -y python3.11-venv git
python3 -m venv .venv
source .venv/bin/activate
pip install --upgrade pip
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Expected console output:

student@instance-1:~$ sudo apt install -y python3.11-venv git
python3 -m venv .venv
source .venv/bin/activate
pip install --upgrade pip
Reading package lists... Done
Building dependency tree... Done
Reading state information... Done
The following additional packages will be installed:
  git-man liberror-perl patch python3-distutils python3-lib2to3 python3-pip-whl python3-setuptools-whl
Suggested packages:
  git-daemon-run | git-daemon-sysvinit git-doc git-email git-gui gitk gitweb git-cvs git-mediawiki git-svn ed diffutils-doc
The following NEW packages will be installed:
  git git-man liberror-perl patch python3-distutils python3-lib2to3 python3-pip-whl python3-setuptools-whl python3.11-venv
0 upgraded, 9 newly installed, 0 to remove and 2 not upgraded.
Need to get 12.4 MB of archives.
After this operation, 52.2 MB of additional disk space will be used.
Get:1 file:/etc/apt/mirrors/debian.list Mirrorlist [30 B]
...redacted...
Installing collected packages: pip
  Attempting uninstall: pip
    Found existing installation: pip 23.0.1
    Uninstalling pip-23.0.1:
      Successfully uninstalled pip-23.0.1
Successfully installed pip-24.0
(.venv) student@instance-1:~$
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Verify Python version.

In the GCE VM execute:

python -V
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Expected console output:

(.venv) student@instance-1:~$ python -V
Python 3.11.2
(.venv) student@instance-1:~$
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Install MCP Toolbox Locally

MCP Toolbox for Databases (later in the text MCP toolbox or toolbox) is an open source MCP server working with different data sources. It helps you to develop tools faster by providing a level of abstraction for different data sources and adding features like authentication and connection pooling. You can read about all the features on the official page.

We are going to use the MCP toolbox to initiate our sample dataset and later to be used as MCP server to handle data source requests from our application during Retrieval Augmented Generation (RAG) flow.

Let's install the MCP toolbox locally to populate the assistantdemo database.

In the GCE VM execute:

export VERSION=0.16.0
curl -O https://storage.googleapis.com/genai-toolbox/v$VERSION/linux/amd64/toolbox
chmod +x toolbox
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Expected console output:

(.venv) student@instance-1:~$ export VERSION=0.16.0
curl -O https://storage.googleapis.com/genai-toolbox/v$VERSION/linux/amd64/toolbox
chmod +x toolbox
  % Total    % Received % Xferd  Average Speed   Time    Time     Time  Current
                                 Dload  Upload   Total   Spent    Left  Speed
100  133M  100  133M    0     0   158M      0 --:--:-- --:--:-- --:--:--  158M
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Run Toolbox for Data Initialization

In the GCE VM execute:

📝Note: If your SSH session was terminated by inactivity or any other reason you need to set your environment variables such as:

export PGPASSWORD=

REGION=us-central1

ADBCLUSTER=alloydb-aip-01

INSTANCE_IP=$(gcloud alloydb instances describe $ADBCLUSTER-pr --cluster=$ADBCLUSTER --region=$REGION --format="value(ipAddress)")

Export environment variables for database population:

export ALLOYDB_POSTGRES_PROJECT=$(gcloud config get-value project)
export ALLOYDB_POSTGRES_REGION="us-central1"
export ALLOYDB_POSTGRES_CLUSTER="alloydb-aip-01"
export ALLOYDB_POSTGRES_INSTANCE="alloydb-aip-01-pr"
export ALLOYDB_POSTGRES_DATABASE="assistantdemo"
export ALLOYDB_POSTGRES_USER="postgres"
export ALLOYDB_POSTGRES_PASSWORD=$PGPASSWORD
export ALLOYDB_POSTGRES_IP_TYPE="private"
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Start toolbox for the database initiation. It will start the process locally which will help you to connect seamlessly to the destination database on AlloyDB to fill it up with sample data.

./toolbox --prebuilt alloydb-postgres
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Expected console output. You should see in the last line of the output - "Server ready to serve!":

student@instance-1:~$ cexport ALLOYDB_POSTGRES_PROJECT=$PROJECT_ID
export ALLOYDB_POSTGRES_REGION="us-central1"
export ALLOYDB_POSTGRES_CLUSTER="alloydb-aip-01"
export ALLOYDB_POSTGRES_INSTANCE="alloydb-aip-01-pr"
export ALLOYDB_POSTGRES_DATABASE="assistantdemo"
export ALLOYDB_POSTGRES_USER="postgres"
export ALLOYDB_POSTGRES_PASSWORD=$PGPASSWORD
export ALLOYDB_POSTGRES_IP_TYPE="private"
student@instance-1:~$ ./toolbox --prebuilt alloydb-postgres
2025-09-02T18:30:58.957655886Z INFO "Using prebuilt tool configuration for alloydb-postgres" 
2025-09-02T18:30:59.507306664Z INFO "Initialized 1 sources." 
2025-09-02T18:30:59.50748379Z INFO "Initialized 0 authServices." 
2025-09-02T18:30:59.507618807Z INFO "Initialized 2 tools." 
2025-09-02T18:30:59.507726704Z INFO "Initialized 2 toolsets." 
2025-09-02T18:30:59.508258894Z INFO "Server ready to serve!"
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Do not exit or close this tab of the Cloud Shell until data population is complete.

Populate Database

Open another Cloud Shell tab using the sign "+" at the top.

And connect to the instance-1 VM:

gcloud compute ssh instance-1 --zone=us-central1-a
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Expected console output:

student@cloudshell:~ (test-project-402417)$ gcloud compute ssh instance-1 --zone=us-central1-a
Linux instance-1 6.1.0-37-cloud-amd64 #1 SMP PREEMPT_DYNAMIC Debian 6.1.140-1 (2025-05-22) x86_64

The programs included with the Debian GNU/Linux system are free software;
the exact distribution terms for each program are described in the
individual files in /usr/share/doc/*/copyright.

Debian GNU/Linux comes with ABSOLUTELY NO WARRANTY, to the extent
permitted by applicable law.
Last login: Tue Sep  2 21:44:07 2025 from 35.229.111.9
student@instance-1:~$
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Clone the GitHub repository with the code for the retrieval service and sample application.

In the GCE VM execute:

git clone  https://github.com/GoogleCloudPlatform/cymbal-air-toolbox-demo.git
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Expected console output:

student@instance-1:~$ git clone  https://github.com/GoogleCloudPlatform/cymbal-air-toolbox-demo.git
Cloning into 'cymbal-air-toolbox-demo'...
remote: Enumerating objects: 3481, done.
remote: Counting objects: 100% (47/47), done.
remote: Compressing objects: 100% (41/41), done.
remote: Total 3481 (delta 16), reused 7 (delta 5), pack-reused 3434 (from 3)
Receiving objects: 100% (3481/3481), 57.96 MiB | 6.04 MiB/s, done.
Resolving deltas: 100% (2549/2549), done.
student@instance-1:~
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Please pay attention if you have any errors.

Prepare Python environment and install requirement packages:

source .venv/bin/activate
cd cymbal-air-toolbox-demo
pip install -r requirements.txt
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Set Python path to the repository root folder and run script to populate the database with the sample dataset. The first command is adding a path to our Python modules to our environment and the second command is populating our database with the data.

export PYTHONPATH=$HOME/cymbal-air-toolbox-demo
python data/run_database_init.py
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Expected console output(redacted). You should see "database init done" at the end:

student@instance-1:~$ source .venv/bin/activate
(.venv) student@instance-1:~$ 
(.venv) student@instance-1:~$ cd cymbal-air-toolbox-demo/
(.venv) student@instance-1:~/cymbal-air-toolbox-demo$ pip install -r requirements.txt
python run_database_init.py
Collecting fastapi==0.115.0 (from -r requirements.txt (line 1))
  Downloading fastapi-0.115.0-py3-none-any.whl.metadata (27 kB)
Collecting google-auth==2.40.3 (from -r requirements.txt (line 2))
  Downloading google_auth-2.40.3-py2.py3-none-any.whl.metadata (6.2 kB)
Collecting google-cloud-aiplatform==1.97.0 (from google-cloud-aiplatform[evaluation]==1.97.0->-r requirements.txt (line 3))
  Downloading google_cloud_aiplatform-1.97.0-py2.py3-none-any.whl.metadata (36 kB)
Collecting itsdangerous==2.2.0 (from -r requirements.txt (line 4))
  Downloading itsdangerous-2.2.0-py3-none-any.whl.metadata (1.9 kB)
Collecting jinja2==3.1.5 (from -r requirements.txt (line 5))
  Downloading jinja2-3.1.5-py3-none-any.whl.metadata (2.6 kB)
Collecting langchain-community==0.3.25 (from -r requirements.txt (line 6))
  Downloading langchain_community-0.3.25-py3-none-any.whl.metadata (2.9 kB)
Collecting langchain==0.3.25 (from -r requirements.txt (line 7))
...

(.venv) student@instance-1:~/cymbal-air-toolbox-demo$ 
(.venv) student@instance-1:~/cymbal-air-toolbox-demo$ export PYTHONPATH=$HOME/cymbal-air-toolbox-demo
python data/run_database_init.py
Airports table initialized
Amenities table initialized
Flights table initialized
Tickets table initialized
Policies table initialized
database init done.
(.venv) student@instance-1:~/cymbal-air-toolbox-demo$
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You can close this tab now.

In the VM session execute:

exit
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And in the Cloud Shell session press ctrl+d or execute :

exit
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In the first tab with running MCP Toolbox press ctrl+c in to exit from the toolbox running session.

The database has been populated with sample data for the application.

You can verify it by connecting to the database and checking the number of rows in the airports table. You can use the psql utility as we've used before or AlloyDB Studio . here is how you can check it using psql

In the ssh session to instance-1 VM execute:

export PGPASSWORD=<Noted AlloyDB password>

REGION=us-central1
ADBCLUSTER=alloydb-aip-01
INSTANCE_IP=$(gcloud alloydb instances describe $ADBCLUSTER-pr --cluster=$ADBCLUSTER --region=$REGION --format="value(ipAddress)")
psql "host=$INSTANCE_IP user=postgres dbname=assistantdemo" -c "SELECT COUNT(*) FROM airports"
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Expected console output:

student@instance-1:~$ REGION=us-central1
ADBCLUSTER=alloydb-aip-01
INSTANCE_IP=$(gcloud alloydb instances describe $ADBCLUSTER-pr --cluster=$ADBCLUSTER --region=$REGION --format="value(ipAddress)")
psql "host=$INSTANCE_IP user=postgres dbname=assistantdemo" -c "SELECT COUNT(*) FROM airports"
 count 
-------
  7698
(1 row)
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The database is ready and we can move on to MCP Toolbox deployment.

You've completed Part 1 of the AlloyDB Agentic RAG application codelab, please continue to Part 2.

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