Gemini Cloud Assist Mcp

Gemini Cloud Assist MCP server

[!IMPORTANT] Private Preview Notice The Gemini Cloud Assist MCP server APIs are currently in Private Preview and are behind an allowlist. Please contact your Google Cloud account team to request access.

[!WARNING] Deprecation Notice & Migration to Remote MCP Server

The Gemini Cloud Assist MCP server has migrated from a local Node.js architecture to a Remote MCP Server architecture. The older local Node.js server will lose support in the coming months.

To use the new Remote MCP Servers, please use version v0.8.0 or later. If you wish to continue using the legacy local server during the transition, please pin your configuration to older versions.

This server connects Model Context Protocol (MCP) clients such as the Gemini CLI to the Gemini Cloud Assist APIs. It allows you to use natural language to understand, manage, and troubleshoot your Google Cloud environment directly from the local command line.

[!NOTE] The Google Cloud Platform Terms of Service (available at https://cloud.google.com/terms/) and the Data Processing and Security Terms (available at https://cloud.google.com/terms/data-processing-terms) do not apply to any component of the Gemini Cloud Assist MCP Server software.

To learn more about Gemini Cloud Assist, see the Gemini Cloud Assist overview in the Google Cloud documentation.

✨ Key features

• Design infrastructure: Create and architect infrastructure configurations for Google Cloud.
• Troubleshoot issues: Run deep investigations to find the root cause of complex issues in your Google Cloud environment.
• Manage resources: Create, update, and delete Google Cloud resources directly from your chat workflow (requires Agent Actions).
• Optimize costs: Analyze your spend, track costs, and identify opportunities for efficiency such as idle resources.
• Get general assistance: Ask questions and get guidance on Google Cloud best practices, architectures, and operations.

Quick start

Before you begin, ensure you have the following set up:

• Google Cloud SDK installed and configured.
• A Google Cloud project.
• The following IAM roles on your user account:
  • roles/serviceusage.serviceUsageAdmin: Required to enable the Cloud Assist APIs.
  • roles/geminicloudassist.user: Required to make requests to the Cloud Assist APIs.

Step 1: Authenticate to Google Cloud

The Gemini Cloud Assist MCP server uses local Application Default Credentials (ADC) to securely authenticate to Google Cloud. To set up ADC, run the following gcloud commands:

# Authenticate your user account to the gcloud CLI
gcloud auth login

# Set up Application Default Credentials for the server.
gcloud auth application-default login

Configure your MCP client

The client-agent configuration depends on which agent you are using.

Gemini CLI

Install the MCP server as a Gemini CLI extension:

gemini extensions install https://github.com/GoogleCloudPlatform/gemini-cloud-assist-mcp

Alternatively, you can manually add the configuration to your ~/.gemini/settings.json:

"mcpServers": {
  "gemini_cloud_assist": {
    "httpUrl": "https://geminicloudassist.googleapis.com/mcp",
    "authProviderType": "google_credentials",
    "oauth": {
      "scopes": ["https://www.googleapis.com/auth/cloud-platform"]
    },
    "timeout": 600000
  },
  "application_design_center": {
    "httpUrl": "https://designcenter.googleapis.com/mcp",
    "authProviderType": "google_credentials",
    "oauth": {
      "scopes": ["https://www.googleapis.com/auth/cloud-platform"]
    },
    "timeout": 600000
  }
}

Antigravity

Add the following to your mcp_config.json:

"mcpServers": {
  "gemini_cloud_assist": {
    "serverUrl": "https://geminicloudassist.googleapis.com/mcp",
    "headers": {},
    "authProviderType": "google_credentials"
  },
  "application_design_center": {
    "serverUrl": "https://designcenter.googleapis.com/mcp",
    "headers": {},
    "authProviderType": "google_credentials"
  }
}

Cursor

1. In your Google Cloud project, create an OAuth 2.0 client ID for a desktop app.
2. Configure URI://anysphere.cursor-mcp/oauth/callback as the redirect URL.
3. Add or merge the following configuration block:

{
  "mcpServers": {
    "gemini_cloud_assist": {
      "url": "https://geminicloudassist.googleapis.com/mcp",
      "auth": {
        "CLIENT_ID": "${env:OAUTH_CLIENT_ID}",
        "CLIENT_SECRET": "${env:OAUTH_CLIENT_SECRET}",
        "scopes": ["https://www.googleapis.com/auth/cloud-platform"]
      }
    },
    "application_design_center": {
      "url": "https://designcenter.googleapis.com/mcp",
      "auth": {
        "CLIENT_ID": "${env:OAUTH_CLIENT_ID}",
        "CLIENT_SECRET": "${env:OAUTH_CLIENT_SECRET}",
        "scopes": ["https://www.googleapis.com/auth/cloud-platform"]
      }
    }
  }
}

Claude

Follow the configuration instructions for your specific application:

• Claude.ai

MCP Tools

Gemini Cloud Assist MCP tools

Gemini Cloud Assist is an agent accessible through a set of MCP tools. The agent invoked by MCP tool calls makes its own tool calls internally to Google Cloud. The following MCP tools are published for agents to consume:

Tool	Description
ask_cloud_assist	The primary interface for Google Cloud assistance and for the Gemini Cloud Assist agent. All functionality is accessible through this tool.
design_infra	Supports workflows for designing and architecting infrastructure on Google Cloud.
investigate_issue	Supports workflows for troubleshooting in Google Cloud. Can do quick troubleshooting or deeper troubleshooting through an Investigation resource.
invoke_operation	Supports workflows for creating, updating, and deleting resources in Google Cloud. Only functional when Agent Actions are enabled.
optimize_costs	Supports workflows for analyzing, tracking, and optimizing Google Cloud costs. Provides breakdowns of spend and identifies opportunities for cost efficiency.

Application Design Center MCP tools

Application Design Center MCP tools, often orchestrated by GCA’s design_infra tool, manages the infrastructure application lifecycle using Application Design Center, including template management, security compliance and remediation and deployment.

Tool	Description
setup_adc	Initializes the Application Design Center environment. This is a one-time setup step that must be performed before other ADC tools can be used.
manage_application	Manages the deployment lifecycle of an application. Use this tool to deploy a verified design using the Application Design Center or retrieve the status and details of an existing deployment. This is the final step that turns your design into a deployed infrastructure on Google Cloud.
manage_application_template	Manages the Infrastructure as Code (IaC) content of your infrastructure design. Use this to save the design as an Application Design Center template, export the design as Terraform files, or update the design (e.g. component, parameters configurations etc).
assess_best_practices	Performs a comprehensive security and configuration audit on your application design before deployment. It validates the design against Security Command Center frameworks and relevant controls, returning a report with actionable findings for remediation.
list_application_templates	Lists all available application designs.

Note: These tools should not be treated as stable APIs. Parameters might be renamed or modified to account for the evolving capabilities of Gemini Cloud Assist.

Agent Skills

The Gemini Cloud Assist MCP tools leverage SKILL.md files to instruct your agent on how to properly use the tools. The skills help to guide your agent on chaining together multiple tools into a workstream, passing relevant local information to Gemini Cloud Assist, and enabling explicit invocation.

Skill	Description
designing-and-deploying-infrastructure	Guides the agent on how to design, assess, deploy, and troubleshoot cloud infrastructure using the Application Design Center (ADC) and Gemini Cloud Assist tools.
operating-google-cloud	Provides instructions for managing Google Cloud Platform (GCP) resources and Kubernetes using specialized MCP tools.

Contributing

• If you encounter a bug, please file an issue on our GitHub Issues page.
• Before sending a pull request, please review our Contributing Guide.

License

This project is licensed under the Apache 2.0 License and provided as-is, without warranty or representation for any use or purpose. For details, see the LICENSE file.