Use the AlloyDB remote MCP server

Preview

This feature is subject to the "Pre-GA Offerings Terms" in the General Service Terms section of the Service Specific Terms, and the Additional Terms for Generative AI Preview Products. Pre-GA features are available "as is" and might have limited support. For more information, see the launch stage descriptions.

Model Context Protocol (MCP) standardizes the way large language models (LLMs) and AI applications or agents connect to outside data sources. MCP servers let you use their tools, resources, and prompts to take actions and get updated data from their backend service.

Local MCP servers typically run on your local machine and use the standard input and output streams (stdio) for communication between services on the same device. Remote MCP servers run on the service's infrastructure and offer an HTTP endpoint to AI applications for communication between the AI MCP client and the MCP server. For more information on MCP architecture, see MCP architecture.

This document describes how to use the AlloyDB remote Model Context Protocol (MCP) server to connect to AlloyDB from AI applications such as Gemini CLI, agent mode in Gemini Code Assist, Claude Code, or in AI applications that you're developing.

Google and Google Cloud remote MCP servers have the following features and benefits:

• Simplified, centralized discovery.
• Managed global or regional HTTP endpoints.
• Fine-grained authorization.
• Optional prompt and response security with Model Armor protection.
• Centralized audit logging.

For information about other MCP servers and information about security and governance controls available for Google Cloud MCP servers, see Google Cloud MCP servers overview.

You might want to use the AlloyDB local MCP server for the following reasons:

• Local development and testing
• Offline MCP use
• Manage AlloyDB clusters and instances from your AI application

For more information about how to use your local MCP server, see Use AlloyDB for PostgreSQL with MCP, Gemini CLI, and other agents.

For more information about how to use our local MCP server, see AlloyDB for PostgreSQL MCP server. The following sections only apply to the AlloyDB for PostgreSQL remote MCP server.

Limitations

The AlloyDB remote MCP server has the following limitations:

• The create_user tool doesn't support creating a built-in authentication user with a password. A user can only be created with IAM authentication.
• If the execute_sql tool returns a response that's larger than 10 MB, then the response might be truncated.
• When you use the execute_sql tool, queries that run for longer than 30 seconds can time out.

Before you begin

Sign in to your Google Cloud account. If you're new to Google Cloud, create an account to evaluate how our products perform in real-world scenarios. New customers also get $300 in free credits to run, test, and deploy workloads.

In the Google Cloud console, on the project selector page, select or create a Google Cloud project.

Roles required to select or create a project

• Select a project: Selecting a project doesn't require a specific IAM role—you can select any project that you've been granted a role on.
• Create a project: To create a project, you need the Project Creator role (roles/resourcemanager.projectCreator), which contains the resourcemanager.projects.create permission. Learn how to grant roles.

Note: If you don't plan to keep the resources that you create in this procedure, create a project instead of selecting an existing project. After you finish these steps, you can delete the project, removing all resources associated with the project.

Go to project selector

If you're using an existing project for this guide, verify that you have the permissions required to complete this guide. If you created a new project, then you already have the required permissions.

Install the Google Cloud CLI.

Note: If you installed the gcloud CLI previously, make sure you have the latest version by running gcloud components update.

If you're using an external identity provider (IdP), you must first sign in to the gcloud CLI with your federated identity.

To initialize the gcloud CLI, run the following command:

gcloud init

In the Google Cloud console, on the project selector page, select or create a Google Cloud project.

Roles required to select or create a project

• Select a project: Selecting a project doesn't require a specific IAM role—you can select any project that you've been granted a role on.
• Create a project: To create a project, you need the Project Creator role (roles/resourcemanager.projectCreator), which contains the resourcemanager.projects.create permission. Learn how to grant roles.

Note: If you don't plan to keep the resources that you create in this procedure, create a project instead of selecting an existing project. After you finish these steps, you can delete the project, removing all resources associated with the project.

Go to project selector

If you're using an existing project for this guide, verify that you have the permissions required to complete this guide. If you created a new project, then you already have the required permissions.

Install the Google Cloud CLI.

Note: If you installed the gcloud CLI previously, make sure you have the latest version by running gcloud components update.

If you're using an external identity provider (IdP), you must first sign in to the gcloud CLI with your federated identity.

To initialize the gcloud CLI, run the following command:

gcloud init

Required roles

To get the permissions that you need to enable the AlloyDB for PostgreSQL MCP server, ask your administrator to grant you the following IAM roles on the project where you want to enable the AlloyDB for PostgreSQL MCP server:

• Service Usage Admin (roles/serviceusage.serviceUsageAdmin)
• Make MCP tool calls: MCP Tool User (roles/mcp.toolUser)
• Create an AlloyDB instance: AlloyDB Admin (roles/alloydb.admin)
• Create an AlloyDB user: AlloyDB Admin (roles/alloydb.admin)
• Execute SQL queries in AlloyDB:
  • AlloyDB Admin (roles/alloydb.admin)
  • Studio Query User (roles/databasesconsole.studioQueryUser)
• Get a AlloyDB instance or list all AlloyDB instances in a project: AlloyDB Viewer (roles/alloydb.viewer)
• List AlloyDB users: AlloyDB Viewer (roles/alloydb.viewer)

For more information about granting roles, see Manage access to projects, folders, and organizations.

These predefined roles contain the permissions required to enable the AlloyDB for PostgreSQL MCP server. To see the exact permissions that are required, expand the Required permissions section:

Required permissions

The following permissions are required to enable the AlloyDB for PostgreSQL MCP server:

• serviceusage.mcppolicy.get
• serviceusage.mcppolicy.update
• Make MCP tool calls: mcp.tools.call
• Create an AlloyDB cluster: alloydb.cluster.create
• Create an AlloyDB user: alloydb.users.create
• Clone an AlloyDB instance: alloydb.instances.create
• Execute SQL queries on an AlloyDB instance:
  • alloydb.instances.executeSql
  • alloydb.instances.login
• Get an AlloyDB cluster: alloydb.instances.get
• Get an AlloyDB cluster operation: alloydb.clusters.get
• Import data to an AlloyDB instance: alloydb.clusters.import
• List AlloyDB clusters in a project: alloydb.clusters.list
• List AlloyDB users: alloydb.users.list
• Update an AlloyDB cluster: alloydb.clusters.update
• Update an AlloyDB user: alloydb.users.update

You might also be able to get these permissions with custom roles or other predefined roles.

Enable or disable the AlloyDB MCP server

You can enable or disable the AlloyDB MCP server in a project with the gcloud beta services mcp enable command. For more information, see the following sections.

Enable the AlloyDB MCP server in a project

Note: After March 17, 2026, the AlloyDB for PostgreSQL remote MCP server is automatically enabled when you enable AlloyDB for PostgreSQL.

If you are using different projects for your client credentials, such as service account keys, OAuth client ID or API keys, and for hosting your resources, then you must enable the AlloyDB service and the AlloyDB remote MCP server on both projects.

To enable the AlloyDB MCP server in your Google Cloud project, run the following command:

gcloud beta services mcp enable SERVICE \
    --project=PROJECT_ID

Replace the following:

• PROJECT_ID: the Google Cloud project ID.
• SERVICE: the global service name for AlloyDB, alloydb.googleapis.com.

The AlloyDB remote MCP server is enabled for use in your Google Cloud Project. If the AlloyDB service isn't enabled for your Google Cloud project, then you're prompted to enable the service before you enable the AlloyDB remote MCP server.

As a security best practice, we recommend that you enable MCP servers only for the services required for your AI application to function.

Disable the AlloyDB MCP server in a project

To disable the AlloyDB MCP server in your Google Cloud project, run the following command:

gcloud beta services mcp disable alloydb.googleapis.com \
    --project=PROJECT_ID

The AlloyDB MCP server is disabled for use in your Google Cloud Project.

Authentication and authorization

AlloyDB MCP servers use the OAuth 2.0 protocol with Identity and Access Management (IAM) for authentication and authorization. All Google Cloud identities are supported for authentication to MCP servers.

The AlloyDB remote MCP server doesn't accept API keys.

We recommend that you create a separate identity for agents using MCP tools so that access to resources can be controlled and monitored. For more information on authentication, see Authenticate to MCP servers.

AlloyDB MCP OAuth scopes

OAuth 2.0 uses scopes and credentials to determine if an authenticated principal is authorized to take a specific action on a resource. For more information about OAuth 2.0 scopes at Google, read Using OAuth 2.0 to access Google APIs.

AlloyDB has the following MCP tool OAuth scopes:

Scope URI for gcloud CLI	Description
https://www.googleapis.com/auth/cloud-platform	Create, update, and list AlloyDB resources including clusters, instances, and database users. Execute SQL queries on AlloyDB clusters.

Additional scopes might be required on the resources accessed during a tool call. To view a list of scopes required for AlloyDB, see AlloyDB Admin API.

Configure an MCP client to use the AlloyDB MCP server

AI applications and agents, such as Claude or Gemini CLI, can instantiate an MCP client that connects to a single MCP server. An AI application can have multiple clients that connect to different MCP servers. To connect to a remote MCP server, the MCP client must know at a minimum the URL of the remote MCP server.

In your AI application, look for a way to connect to a remote MCP server. You are prompted to enter details about the server, such as its name and URL.

For the AlloyDB remote MCP server, enter the following as required:

• Server name: AlloyDB MCP server
• Endpoint: https://alloydb.REGION.rep.googleapis.com/mcp
• Transport: HTTP
• Authentication details: Depending on how you want to authenticate, you can enter your Google Cloud credentials, your OAuth Client ID and secret, or an agent identity and credentials. For more information on authentication, see Authenticate to MCP servers.
• OAuth scope: the OAuth 2.0 scope that you want to use when connecting to the AlloyDB for PostgreSQL MCP server.

For host specific guidance, see the following:

• Claude.ai
• Gemini CLI

For more general guidance, see the following resources:

• Connect to remote MCP servers.
• Configure MCP in an AI application.

Available tools

To view details of available MCP tools and their descriptions for the AlloyDB MCP server, see the AlloyDB MCP reference.

List tools

Use the MCP inspector to list tools, or send a tools/list HTTP request directly to the AlloyDB for PostgreSQL remote MCP server. The tools/list method doesn't require authentication. You must provide a string or numeric ID—for example, 1 or my-id.

POST /mcp HTTP/1.1
Host: alloydb.googleapis.com
Content-Type: application/json

{
  "id": USER_SPECIFIED_ID,
  "jsonrpc": "2.0",
  "method": "tools/list",
}

Execute SQL

To execute SQL statements, follow these steps:

1. Set the data_api_access instance setting on the AlloyDB instance to the value ALLOW_DATA_API_ACCESS. When you create an instance using the create_instance tool, the data_api_access configuration is enabled automatically.

   If the data_api_access configuration isn't enabled on an instance, you can enable it using the curl command to update the value of the field dataApiAccess to ENABLED:

   curl -X PATCH \
    -H "Authorization: Bearer $(gcloud auth print-access-token)" \
    -H "Content-Type: application/json" \
    https://alloydb.googleapis.com/v1alpha/projects/PROJECT_ID/locations/LOCATION/clusters/CLUSTER_ID/instances/INSTANCE_ID?updateMask=dataApiAccess \
    -d '{
      "dataApiAccess": "ENABLED",
    }'
   

   Replace the following:

   • PROJECT_ID: The ID of your Google Cloud project.
   • LOCATION: The region where your AlloyDB cluster is located.
   • CLUSTER_ID: The ID of your AlloyDB cluster.
   • INSTANCE_ID: The ID of your AlloyDB instance.

2. In the Gemini CLI, enter a prompt similar to the following:

   Enable IAM database authentication on the AlloyDB instance INSTANCE_NAME Make sure that the SQL statements use the privileges associated with the IAM database authentication user account USER_ACCOUNT

   Replace the following:

   • INSTANCE_NAME: the name of the AlloyDB instance.
   • USER_ACCOUNT: the IAM user account to use for authentication when executing SQL statements.

Sample use cases

The following are sample use cases for the AlloyDB MCP server.

Web application development

A sample use case might be the rapid development of web applications and the provisioning of AlloyDB instances as their source database. In this use case, using the AlloyDB MCP server lets you build a new database and populate it with initial data for a new project using natural language.

Sample prompt:

Create a new PostgreSQL development instance and set up a table called products.

Workflow: the workflow for setting up a web application might look like the following:

• Provisioning: The agent creates a cluster that the instance can be allocated in. The agent then calls the create_instance tool to create a new AlloyDB instance with development environment-sized specifications.

• Verification: The agent uses the get_operation tool to poll the status of the instance creation operation.

• Connection: When the operation is complete, the agent uses the get_instance tool to retrieve the instance connection metadata.

• Schema setup: The agent creates the database and then uses the execute_sql to run the CREATE TABLE products SQL statement.

• Data seeding: The agent uses execute_sql again to insert initial seed data (DML) into the newly created table.

Operational and database configuration management

In this sample use case, you might review existing database instances to help ensure they meet operational configuration standards. You can also use the agent to manage database users on the instance.

Sample prompt:

List all the PostgreSQL instances in my project and show me their details to verify that they're using the same configuration and that the most recent list database users has been successfully updated.

Workflow: the workflow for checking AlloyDB instance and database user configuration might look like the following.

• Discovery: The agent uses list_instances to retrieve a list of all AlloyDB instances in the project.

• Inspection: For each instance identified, the agent calls get_instance to fetch detailed configuration metadata, such as the database version, region, and machine type, and calls list_users to check the database users on the instance.

• Reporting: The agent summarizes the findings, highlighting any instances or users that deviate from the expected configuration.

Optional security and safety configurations

MCP introduces new security risks and considerations due to the wide variety of actions that can be taken with MCP tools. To minimize and manage these risks, Google Cloud offers defaults and customizable policies to control the use of MCP tools in your Google Cloud organization or project.

For more information about MCP security and governance, see AI security and safety.

Model Armor

Model Armor is a Google Cloud service designed to enhance the security and safety of your AI applications. It works by proactively screening LLM prompts and responses, protecting against various risks and supporting responsible AI practices. Whether you are deploying AI in your cloud environment, or on external cloud providers, Model Armor can help you prevent malicious input, verify content safety, protect sensitive data, maintain compliance, and enforce your AI safety and security policies consistently across your diverse AI landscape.

Model Armor is only available in specific regional locations. If Model Armor is enabled for a project, and a call to that project comes from an unsupported region, then Model Armor makes a cross-regional call. For more information, see Model Armor locations.

Caution: Model Armor logs the entire payload if a request fails. This might expose sensitive information in the logs.

Enable Model Armor

To enable Model Armor, complete the following steps:

To enable Model Armor on your Google Cloud project, run the following gcloud CLI command:

gcloud services enable modelarmor.googleapis.com \
    --project=PROJECT_ID

Replace PROJECT_ID with your Google Cloud project ID.

Configure protection for Google and Google Cloud remote MCP servers

To protect your MCP tool calls and responses, you create a Model Armor floor setting and then enable MCP content security for your project. A floor setting defines the minimum security filters that apply across the project. This configuration applies a consistent set of filters to all MCP tool calls and responses within the project.

Tip: Don't enable the prompt injection and jailbreak filter unless your MCP traffic carries natural language data.

1. Set up a Model Armor floor setting with MCP sanitization enabled. For more information, see Configure Model Armor floor settings.

   Note: If the agent and the MCP server are in different projects, you can create floor settings in both projects (the client project and the resource project). In this case, Model Armor is invoked twice, once for each project.

   See the following example command:

   gcloud model-armor floorsettings update \
   --full-uri='projects/PROJECT_ID/locations/global/floorSetting' \
   --enable-floor-setting-enforcement=TRUE \
   --add-integrated-services=GOOGLE_MCP_SERVER \
   --google-mcp-server-enforcement-type=INSPECT_AND_BLOCK \
   --enable-google-mcp-server-cloud-logging \
   --malicious-uri-filter-settings-enforcement=ENABLED \
   --add-rai-settings-filters='[{"confidenceLevel": "HIGH", "filterType": "DANGEROUS"}]'

   Replace PROJECT_ID with your Google Cloud project ID.

   Note the following settings:

   • INSPECT_AND_BLOCK: The enforcement type that inspects content for the Google MCP server and blocks prompts and responses that match the filters.
   • ENABLED: The setting that enables a filter or enforcement.
   • HIGH: The confidence level for the Responsible AI - Dangerous filter settings. You can modify this setting, though lower values might result in more false positives. For more information, see Configure floor settings.

2. For your project, enable Model Armor protection for remote MCP servers.

   gcloud beta services mcp content-security add modelarmor.googleapis.com --project=PROJECT_ID

   Replace PROJECT_ID with your Google Cloud project ID. After you run this command, Model Armor sanitizes all MCP tool calls and responses from the project, regardless of where the calls and responses originate.

3. To confirm that Google MCP traffic is sent to Model Armor, run the following command:

   gcloud beta services mcp content-security get --project=PROJECT_ID
   

   Replace PROJECT_ID with the Google Cloud project ID.

Disable Model Armor for MCP in a project

To disable Model Armor on a Google Cloud project, run the following command:

gcloud beta services mcp content-security remove modelarmor.googleapis.com \
    --project=PROJECT_ID

Replace PROJECT_ID with the Google Cloud project ID.

Google MCP traffic won't be scanned by Model Armor for the specified project.

Disable scanning MCP traffic with Model Armor

If you want to use Model Armor in a project, and you want to stop scanning Google MCP traffic with Model Armor, run the following command:

gcloud model-armor floorsettings update \
  --full-uri='projects/PROJECT_ID/locations/global/floorSetting' \
  --remove-integrated-services=GOOGLE_MCP_SERVER

Replace PROJECT_ID with the Google Cloud project ID.

Model Armor won't scan MCP traffic in the project.

Control MCP use with IAM deny policies

Identity and Access Management (IAM) deny policies help you secure Google Cloud remote MCP servers. Configure these policies to block unwanted MCP tool access.

For example, you can deny or allow access based on:

• The principal.
• Tool properties like read-only.
• The application's OAuth client ID.

For more information, see Control MCP use with Identity and Access Management

What's next

• Read the AlloyDB MCP reference documentation.
• Learn more about Google Cloud MCP servers.