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  3. Gemini Cloud Assist Mcp
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Health: ActiveRecent health check succeeded.Last checked 8/11/2026, 12:01:07 AM

Gemini Cloud Assist Mcp

Enrichment pendingWe haven’t run our AI enrichment pass on this listing yet, so the overview, use cases, and FAQ below may be sparse or missing. We work through the catalog over time — check back soon.
View Repository65 GitHub StarsTotal stargazers on GitHub for the source repository (65 stars).

MCP Server for understanding, managing & troubleshooting your GCP environment.

Quick Install

Automated & IDE Setup

Copy the AI prompt to install this server into Claude Code, Cursor, or another agent — or use 1-click editor setup below.

Add to CursorAdd to VS Code
Manual Client & Custom JSON ConfigExpand JSON ▾

Install Config Generator

Choose your client
claude_desktop_config.json
{
  "mcpServers": {
    "gemini-cloud-assist-mcp": {
      "command": "npx",
      "args": [
        "-y",
        "gemini-cloud-assist-mcp"
      ]
    }
  }
}

💡 Paste into ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or %APPDATA%\Claude\claude_desktop_config.json (Windows)

Install Tool Schemas (5) Directory Badge Claim listing Alternatives☁️ More in Cloud Platforms

Capabilities & Tool Schemas (5) ~270 tokensApproximate context cost of this server’s tool schemas (~4 chars/token), before any tool is called. Actual usage depends on your client and model.Self-reported Self-reportedParsed from the repository README, not verified against a live server — may be incomplete or out of date.

Inspect callable tools, capabilities, and parameters exposed to AI agents by Gemini Cloud Assist Mcp.

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.

Documentation Overview

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.

npm @google-cloud/gemini-cloud-assist-mcp package

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:

shell
# 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:

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

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

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:

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:
config.json
{
  "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:

ToolDescription
ask_cloud_assistThe primary interface for Google Cloud assistance and for the Gemini Cloud Assist agent. All functionality is accessible through this tool.
design_infraSupports workflows for designing and architecting infrastructure on Google Cloud.
investigate_issueSupports workflows for troubleshooting in Google Cloud. Can do quick troubleshooting or deeper troubleshooting through an Investigation resource.
invoke_operationSupports workflows for creating, updating, and deleting resources in Google Cloud. Only functional when Agent Actions are enabled.
optimize_costsSupports 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.

ToolDescription
setup_adcInitializes the Application Design Center environment. This is a one-time setup step that must be performed before other ADC tools can be used.
manage_applicationManages 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_templateManages 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_practicesPerforms 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_templatesLists 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.

SkillDescription
designing-and-deploying-infrastructureGuides 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-cloudProvides 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.

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Frequently Asked Questions about Gemini Cloud Assist Mcp

Add the following block to your claude_desktop_config.json under mcpServers: "mcpServers": { "gemini-cloud-assist-mcp": { "command": "npx", "args": ["-y", "gemini-cloud-assist-mcp"] } }

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Technical Specs & Signals

Category☁️Cloud Platforms
More technical detailsExpand ▾
TransportSTDIO
RuntimeNode.js
Views0
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Installs0
Installs & Copy ActionsTotal times users copied install commands or configuration snippets for this server.
GitHub stars65
GitHub Star CountTotal stargazers on GitHub representing community popularity (65 stars).
Last commit2mo ago
Last Repository CommitThe most recent commit or push recorded for this server's GitHub repository.Last commit on May 20, 2026
npm downloads18/mo
Monthly npm DownloadsAverage monthly package installs recorded from npm registry statistics.
49Quality signal: Fair · 49/100How this signal is calculated ▾
Server availabilityNot measured

Not scored for repo-hosted servers — we can't reach the running server, only its GitHub page. Hosted MCP endpoints are health-checked live.

Verified ownership10/20
Documentation & tools20/30
Adoption & activity7/15
Community engagement0/10

A guidance signal from public completeness & health data — not a user rating. New listings start lower and rise as they add docs, get verified, and grow adoption. Signals we can't observe for a listing are skipped, not counted against it.

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