Use the Google SecOps 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 Google Security Operations remote MCP server to connect to Google SecOps from AI applications such as Gemini CLI, agent mode in Gemini Code Assist, Claude Code, or in AI applications 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.

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.

Verify that billing is enabled for your Google Cloud project.

Enable the Chronicle API.

Roles required to enable APIs

To enable APIs, you need the Service Usage Admin IAM role (roles/serviceusage.serviceUsageAdmin), which contains the serviceusage.services.enable permission. Learn how to grant roles.

Enable the API

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.

Verify that billing is enabled for your Google Cloud project.

Enable the Chronicle API.

Roles required to enable APIs

To enable APIs, you need the Service Usage Admin IAM role (roles/serviceusage.serviceUsageAdmin), which contains the serviceusage.services.enable permission. Learn how to grant roles.

Enable the API

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

Note: Make sure you are on the Google Cloud platform. Customers using SOAR APIs need to migrate to Google Cloud before using Google Cloud MCP servers.

Required roles

To set up and use the Google SecOps remote MCP server, you need the following IAM roles:

• The MCP tool user (roles/mcp.toolUser) role is required for calling tools on any MCP server enabled by the parent project.
• The Chronicle API admin (roles/chronicle.admin) role is required to ensure full access to the Chronicle API services, including global settings.
• The Chronicle SOAR Admin(roles/chronicle.soarAdmin) role is required to grant admin access to Google SecOps.

Enable the Google SecOps MCP server in a project

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 Google SecOps service and the Google SecOps remote MCP server on both projects.

To enable the Google SecOps 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 or regional service name for Google SecOps. For example, chronicle.googleapis.com or chronicle.us-central1.rep.googleapis.com. For available regions, see the Google Security Operations MCP reference.

The Google SecOps remote MCP server is enabled for use in your Google Cloud Project. If the Google SecOps service isn't enabled for your Google Cloud project, you are prompted to enable the service before enabling the Google SecOps 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 Google SecOps MCP server in a project

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

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

The Google SecOps MCP server is disabled for use in your Google Cloud project.

Authentication and authorization

Google SecOps 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.

We recommend creating 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.

Google SecOps 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.

Google SecOps has the following MCP tool OAuth scope:

Scope URI for gcloud CLI	Description
https://www.googleapis.com/auth/chronicle.read-write	Allows access to read and modify data.

Configure an MCP client to use the Google SecOps 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 Google SecOps MCP server, enter the following as required:

• Server name: Google SecOps MCP server
• Server URL or Endpoint: chronicle.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 Google SecOps MCP server. For Google SecOps, use https://www.googleapis.com/auth/chronicle.

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

MCP Tools that are read-only have the MCP attribute mcp.tool.isReadOnly set to true. You might want to only allow read-only tools in certain environments through your organization policy.

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

List tools

Use the MCP inspector to list tools, or send a tools/list HTTP request directly to the Google Security Operations remote MCP server. The tools/list method doesn't require authentication.

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

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

Sample use cases

The following are sample use cases for the Google SecOps MCP server:

Tool: list_rule_errors

Sample prompt:

List rule errors for the rule: ru_ddd45753-d749-4fee-b068-29072e750cfb

Response:

Here are the rule errors for ru_ddd45753-d749-4fee-b068-29072e750cfb:

Error Message: query took too long to execute, see https://cloud.google.com/chronicle/docs/detection/yara-l-best-practices for tips for optimizing rules; these optimization tips are applicable to various types of queries

Time Range: 2025-02-16T10:00:00Z to 2025-02-16T11:00:00Z
Rule: projects/935934211738/locations/US/instances/eb3b937b-3ab6-47e5-8185-24837b826691/rules/ru_ddd45753-d749-4fee-b068-29072e750cfb@v_1740004374_748943000
Error Message: query took too long to execute, see https://cloud.google.com/chronicle/docs/detection/yara-l-best-practices for tips for optimizing rules; these optimization tips are applicable to various types of queries

Time Range: 2025-02-16T11:00:00Z to 2025-02-16T12:00:00Z
Rule: projects/935934211738/locations/US/instances/eb3b937b-3ab6-47e5-8185-24837b826691/rules/ru_ddd45753-d749-4fee-b068-29072e750cfb@v_1740004374_748943000
The errors indicate that the queries for this rule took too long to execute during the specified time ranges. You may want to review the YARA-L best practices for optimizing rules.

Tool: create_rules

Sample prompt:

Create the following rule:
successful_user_logins_from_outside_us_test {
meta:
author = "Google SecOps Gemini"
description = "Detect successful user logins originating from outside the United States."
severity = "Medium"
events:
$e.metadata.event_type = "USER_LOGIN"
$e.security_result.action = "ALLOW"
$e.principal.ip_geo_artifact.location.country_or_region != "United States"
outcome:
$user = array($e.principal.user.userid)
$source_ip = array($e.principal.ip)
$country = array($e.principal.ip_geo_artifact.location.country_or_region)
$city = array($e.principal.ip_geo_artifact.location.city)
condition:
$e
}

Response:

The rule successful_user_logins_from_outside_us_test has been successfully created with the following details:

Name: projects/935934211738/locations/US/instances/eb3b937b-3ab6-47e5-8185-24837b826691/rules/ru_cff9cae1-bb88-4456-b725-4c08f21803ed
Revision ID: v_1768208899_054095000
Display Name: successful_user_logins_from_outside_us_test
Author: Google SecOps Gemini
Description: Detect successful user logins originating from outside the United States.
Severity: Medium
Compilation State: SUCCEEDED
Create Time: 2026-01-12T09:08:19.054095Z

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, 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 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.

Organization level MCP control

You can create custom organization policies to control the use of MCP servers in your Google Cloud organization using the gcp.managed.allowedMCPService constraint. For more information and usage examples, see Google Cloud MCP servers Access control with IAM.

What's next

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