io.github.GoogleCloudPlatform/gemini-cloud-assist-mcp MCP Server
io.github.GoogleCloudPlatform/gemini-cloud-assist-mcp
AI-powered Google Cloud management, troubleshooting, and infrastructure design via natural language.
What is the io.github.GoogleCloudPlatform/gemini-cloud-assist-mcp MCP server?
The Gemini Cloud Assist MCP server connects Claude, Cursor, and other MCP clients to Google Cloud's Gemini Cloud Assist APIs, enabling natural language understanding, management, and troubleshooting of GCP environments. It supports infrastructure design, issue investigation, resource management, cost optimization, and general cloud guidance.
This server brings AI-assisted cloud operations to your command line and IDE. Use natural language to design infrastructure, troubleshoot complex issues, manage resources, optimize costs, and get guidance on Google Cloud best practices—all without leaving your chat interface.
How to install io.github.GoogleCloudPlatform/gemini-cloud-assist-mcp
Copy-paste configuration for popular MCP clients.
Tools & capabilities
Tools this server exposes to the agent.
ask_cloud_assist— Primary interface for Google Cloud assistance; all functionality accessible through this tool.design_infra— Supports workflows for designing and architecting infrastructure on Google Cloud.investigate_issue— Supports troubleshooting workflows in Google Cloud with quick or deep investigation capabilities.invoke_operation— Supports creating, updating, and deleting Google Cloud resources (requires Agent Actions enabled).optimize_costs— Analyzes spend, tracks costs, and identifies efficiency opportunities such as idle resources.setup_adc— Initializes the Application Design Center environment for infrastructure deployment.manage_application— Manages deployment lifecycle of applications using Application Design Center.manage_application_template— Manages Infrastructure as Code content, templates, and design configurations.assess_best_practices— Performs security and configuration audit on application designs before deployment.list_application_templates— Lists all available application designs.
Use cases
- Design and architect cloud infrastructure using natural language prompts
- Troubleshoot complex issues in your GCP environment with AI-guided investigation
- Create, update, and delete Google Cloud resources directly from chat
- Analyze cloud spending and identify cost optimization opportunities
- Deploy verified infrastructure designs using Application Design Center
- Validate application designs against security and compliance frameworks
io.github.GoogleCloudPlatform/gemini-cloud-assist-mcp MCP server FAQ
It's an MCP server that connects AI agents (Claude, Cursor, etc.) to Google Cloud's Gemini Cloud Assist APIs, enabling natural language-based cloud management, troubleshooting, infrastructure design, and cost optimization.
The server is open-source (Apache 2.0), but access to the Gemini Cloud Assist APIs is currently in Private Preview and requires allowlist approval from your Google Cloud account team.
Create an OAuth 2.0 client ID in your GCP project, set the redirect URL to `URI://anysphere.cursor-mcp/oauth/callback`, then add the configuration block to Cursor's MCP settings with your CLIENT_ID and CLIENT_SECRET.
Follow the configuration instructions in the README for Claude.ai, which involves setting up OAuth credentials and adding the server URL to your Claude configuration.
You need Google Cloud SDK installed, a GCP project, and IAM roles: `roles/serviceusage.serviceUsageAdmin` and `roles/geminicloudassist.user`. Authentication uses Application Default Credentials (ADC) via `gcloud auth application-default login`.
The server has migrated to a Remote MCP Server architecture (v0.8.0+). The older local Node.js version will lose support; users should upgrade to v0.8.0 or later.
README (reference)
Source of truth, from the repository.
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
v0.8.0or 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
- In your Google Cloud project, create an OAuth 2.0 client ID for a desktop app.
- Configure
URI://anysphere.cursor-mcp/oauth/callbackas the redirect URL. - 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:
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.
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