Manage MCP servers

Model Context Protocol (MCP) servers and their tools enable your AI applications to connect with databases, calendars, productivity tools, APIs, and other agents. This guide explains how to list MCP servers and tools, authenticate your AI applications to MCP servers, and configure optional security and safety settings for MCP usage.

Google and Google Cloud services are available as remote MCP servers that run on our infrastructure, not your machine. For more information, see Google Cloud MCP servers overview.

This guide is for developers who want to use Google and Google Cloud MCP server tools in their AI applications, and for users of AI assistance applications such as Claude Code, Gemini Code Assist, Gemini CLI, or Google AI Studio who want to use Google and Google Cloud MCP server tools to streamline their workflow.

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.

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

Create or select 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.

Create a Google Cloud project:
```
gcloud projects create PROJECT_ID
```
Replace PROJECT_ID with a name for the Google Cloud project you are creating.
Select the Google Cloud project that you created:
```
gcloud config set project PROJECT_ID
```
Replace PROJECT_ID with your Google Cloud project name.

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.

Verify that billing is enabled for your Google Cloud project.

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

Create or select 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.

Create a Google Cloud project:
```
gcloud projects create PROJECT_ID
```
Replace PROJECT_ID with a name for the Google Cloud project you are creating.
Select the Google Cloud project that you created:
```
gcloud config set project PROJECT_ID
```
Replace PROJECT_ID with your Google Cloud project name.

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.

Verify that billing is enabled for your Google Cloud project.

Install the Google Cloud CLI beta component:
```
gcloud components install beta
```

Required roles

To get the permissions that you need to enable and use MCP servers, ask your administrator to grant you the following IAM roles:

Enable MCP servers: Service Usage Admin (roles/serviceusage.serviceUsageAdmin) on the Google Cloud project
Make MCP tool calls to Google and Google Cloud MCP tools: MCP Tool User (roles/mcp.toolUser) on the Google Cloud project

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

These predefined roles contain the permissions required to enable and use MCP servers. To see the exact permissions that are required, expand the Required permissions section:

Required permissions

The following permissions are required to enable and use MCP servers:

Enable MCP servers:
- serviceusage.mcppolicy.get
- serviceusage.mcppolicy.update
Make MCP tool calls to Google and Google Cloud MCP tools:
- mcp.tools.call
- resourcemanager.projects.get
- resourcemanager.projects.list

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

Enable MCP servers

To enable Google and Google Cloud remote MCP servers, you need to get the service name by listing available MCP servers. You must enable MCP servers in your Google Cloud project before using them in your AI applications. AI applications use Google credentials to authenticate to enabled Google and Google Cloud remote MCP servers.

If your AI application and Google Cloud resources are in different projects, you must enable the service and the service's MCP server in both the application project and the resource project.

If you have a Google Cloud organization, then your administrator can control MCP usage with an organization policy. For more information about Google Cloud organization policy control of MCP, see Control MCP use in a Google Cloud organization.

Available MCP servers

Available Google and Google Cloud remote MCP servers are listed in Supported products.

List enabled MCP servers

To list enabled MCP servers for your project, run the following command:

gcloud beta services mcp list --enabled

The response resembles the following:

NAME: services/bigquery.googleapis.com
MCP_ENDPOINT: bigquery.googleapis.com/mcp

NAME: services/mapstools.googleapis.com
MCP_ENDPOINT: mapstools.googleapis.com/mcp

List available tools

To get a list of available tools and their descriptions, MCP clients use the MCP tools/list method in an HTTP request to the MCP server endpoint. Authentication isn't required for the tools/list method.

POST /mcp HTTP/1.1
Host: SERVICE_NAME
Content-Type: application/json

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

Replace SERVICE_NAME with the service name—for example, the BigQuery service name is bigquery.googleapis.com. For information about listing service names for available MCP servers, see List available MCP servers. To see a list of Google and Google Cloud services that have remote MCP servers without running commands, see Supported products.

You can send an HTTP request to list tools directly to a Google remote MCP server with the following command:

curl -X POST \
  -H "Content-Type: application/json" \
  -d '{"jsonrpc": "2.0", "id":0, "method": "tools/list"}' \
  "https://SERVICE_NAME/mcp"

The response resembles the following:

{
  "jsonrpc": "2.0",
  "id": 1,
  "result": {
    "tools": [
      {
        "name": "list_topics",
        "title": "List Topics",
        "description": "Get list of available topics.",
        "input_schema": {...}
        "output_schema": {...}
      },
      {
        "name": "get_topic",
        "title": "Get Topic",
        "description": "Get messages in a Topic.",
        "input_schema": {...}
        "output_schema": {...}
      },
      ...
    ]
  }
}

Authenticate your AI application

Once you have enabled an MCP server in your project, you can use your Google credentials to authenticate and use its tools through your AI application. For safety and observability, you might want to create a separate identity with specific permissions for your application instead of using your own permissions if you are working with production resources. For more information, see Authenticate to MCP servers.

Optional security and safety configurations

MCP tools can take a wide variety of actions on behalf of AI applications, introducing security risks and considerations. To help you minimize and manage these risks, Google Cloud provides default and customizable policies that control how MCP tools are used within your Google Cloud organization or project. For more information about MCP security and governance, see AI security and safety.

Enable 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 ensuring responsible AI practices. Whether you are deploying AI in your Google Cloud environment, or even 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, Model Armor makes a cross-regional call. For more information, see Model Armor locations.

To enable Model Armor, complete the steps in Configure Model Armor protection for Google and Google Cloud MCP servers.

Model Armor logging

For information about Model Armor audit and platform logs, see Model Armor audit logging.

Use MCP servers

To use Google and Google Cloud remote MCP server tools, AI applications must have the MCP Tool User role (roles/mcp.toolUser) and the necessary service permissions for the tool's Google Cloud service.

To grant the MCP Tool User role, run the following command:

gcloud projects add-iam-policy-binding PROJECT_ID \
    --member="PRINCIPAL" \
    --role="roles/mcp.toolUser"

Replace the following:

PROJECT_ID: the Google Cloud project.
PRINCIPAL: the principal identifier for the identity you are granting the MCP Tool User role to. For information about the types of principals available on Google Cloud, see Identity and Access Management (IAM) Principals.

What's next

Learn about access control with IAM.
Control MCP use in a Google Cloud organization.

Manage MCP servers Stay organized with collections Save and categorize content based on your preferences.

Before you begin

Required roles

Required permissions

Enable MCP servers

Available MCP servers

List enabled MCP servers

List available tools

Authenticate your AI application

Optional security and safety configurations

Enable Model Armor

Model Armor logging

Use MCP servers

What's next

Manage MCP servers