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Gemini Cloud Assist MCP
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Gemini Cloud Assist MCP

The Gemini Cloud Assist MCP server is a tool that connects MCP clients with the Google Cloud Gemini Cloud Assist API, allowing users to understand, manage, and troubleshoot Google Cloud environment issues using natural language.
Cloud platformDeveloper tools#Cloud service#Fault troubleshooting#Resource management#AI assistant.TypeScript
2.5 points
5.9K
Open Site

Overview

Installation

Content Details

Alternatives

What is Gemini Cloud Assist MCP Server?

This is an intelligent connector that links AI assistants (such as Gemini CLI, Claude, etc.) with the Google Cloud platform. Through natural language conversations, you can directly query the status of cloud resources, troubleshoot issues, and analyze performance without memorizing complex command - line or console operations.

How to use Gemini Cloud Assist?

Simply configure the MCP server in a supported AI client, and then ask questions related to the cloud environment just like chatting with an assistant. The system will automatically convert your questions into cloud platform queries and return the results in an easy - to - understand manner.

Use cases

Suitable for users such as developers, operations engineers, and cloud administrators who need to frequently interact with Google Cloud. It is particularly applicable to daily operation and maintenance tasks such as rapid fault troubleshooting, resource status checking, and performance analysis.

Main features

Intelligent problem investigation
Create and run automated investigations to deeply analyze complex issues in the cloud environment and automatically locate the root cause.
Resource search and analysis
Use natural language to search for and analyze Google Cloud resources and quickly obtain status and performance information.
Iterative analysis
Add new observation information during the investigation process, continuously optimize the analysis results, and obtain more accurate problem diagnosis.
Cross - service integration
Support unified queries for multiple Google Cloud services such as GKE, Compute Engine, and Cloud Storage.
Advantages
Natural language interaction: No need to memorize complex commands. Manage cloud resources through conversations.
Rapid fault troubleshooting: Automated problem analysis significantly shortens the problem - solving time.
Unified query interface: Query the status of multiple cloud services through a single entry.
Intelligent recommendation: Provide specific repair suggestions and operation guidance based on the analysis results.
Security authentication: Use standard Google Cloud authentication to ensure access security.
Limitations
Dependent on the Google Cloud environment: Only support Google Cloud platform services.
Requires permission configuration: Appropriate IAM roles and API enablement need to be configured in advance.
Network requirements: A stable network connection is required to access the cloud API.
Learning curve: Initial configuration requires an understanding of MCP client settings.

How to use

Environment preparation
Ensure that Node.js v20+ , Git, and Google Cloud SDK are installed, and you have a valid Google Cloud project.
Identity authentication
Use the gcloud command - line tool to complete user login and application default credential settings.
Configure the MCP client
Add the Gemini Cloud Assist MCP server configuration to your preferred AI client.
Start using
Restart the client and start querying and managing your Google Cloud resources using natural language.

Usage cases

Troubleshoot insufficient resources in the GKE cluster
When pods in the GKE cluster are in the pending state, quickly diagnose resource bottleneck issues.
Analyze cloud storage space issues
Diagnose the problem of pod crashes caused by the exhaustion of ephemeral storage on GKE nodes.
Query resource inventory
Quickly obtain detailed inventory and status of resources such as GKE node pools and virtual machine instance groups.

Frequently Asked Questions

What permissions are required to use this service?
Which AI clients are supported?
How is data security ensured?
Are the results of the investigation analysis accurate?
What should I do if I encounter configuration issues?

Related resources

Official GitHub repository
Get the latest code, submit issues, and participate in contributions.
Gemini Cloud Assist documentation
Understand the detailed functions of the Gemini Cloud Assist API.
Model Context Protocol official website
Understand the technical specifications and design concepts of the MCP protocol.
Google Cloud IAM guide
Learn how to configure appropriate IAM roles and permissions.
npm package page
View package version information and installation statistics.

Installation

Copy the following command to your Client for configuration
"mcpServers" : {
   "GeminiCloudAssist": {
     "command": "npx",
     "args": ["-y", "@google-cloud/gemini-cloud-assist-mcp@latest"],
     "timeout": 600000
   }
}
Note: Your key is sensitive information, do not share it with anyone.

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