G

GCP

The GCP MCP Server is a standardized AI assistant interface for querying and managing Google Cloud Platform resources
2.5 points
14

What is the Google Cloud Platform MCP Server?

The Google Cloud Platform MCP Server is a standardized interface that allows AI assistants to interact with Google Cloud services through the Model Context Protocol (MCP). It supports querying, managing, and optimizing your GCP resources.

How to use the Google Cloud Platform MCP Server?

You can start the server with simple commands and manage GCP resources as needed, such as creating instances and monitoring logs.

Applicable Scenarios

Suitable for enterprises and individual developers who need to efficiently manage and optimize Google Cloud resources, especially users who hope to improve work efficiency with the help of AI assistants.

Main Features

Container and Package ManagementManage container images and other software packages through Artifact Registry.
Data Analysis and QueryUse BigQuery to quickly build complex data analysis queries.
Audit Log AnalysisView and analyze Cloud Audit Logs to track operation records.
CI/CD Pipeline ManagementAutomate the build, test, and deployment processes using Cloud Build.
Virtual Machine Instance ManagementEasily create, configure, and manage Compute Engine instances.
Performance MonitoringMonitor cloud resource performance in real - time and set up alert notifications.
Serverless DeploymentQuickly deploy and manage serverless applications.
Object Storage ManagementEfficiently store and retrieve large amounts of data.

Advantages and Limitations

Advantages
Simplify complex GCP operation processes
Support integration of multiple mainstream GCP services
Achieve intelligent resource management through AI assistants
Limitations
Require appropriate GCP permission configuration
May have certain dependence on the network environment

How to Use

Install the MCP Server
Clone the code repository and install the required dependencies.
Configure Environment Variables
Set necessary environment variables such as GCP_PROJECT_ID and GOOGLE_APPLICATION_CREDENTIALS.
Start the Server
Run the main script to start the MCP server.

Usage Examples

Query all Compute Engine instancesGet the status of Compute Engine instances in the current project.
Deploy a new Cloud Run serviceUse the MCP server to deploy a simple Hello World service.

Frequently Asked Questions

How to ensure the secure use of the MCP server?
Does it support other GCP services?

Related Resources

Official Documentation
Learn about various Google Cloud services.
GitHub Repository
Access the open - source code repository.
Installation
Copy the following command to your Client for configuration
"mcpServers": {
  "GCP Cloud Tools": {
    "command": "uv",
    "args": [
      "run",
      "--with",
      "google-cloud-artifact-registry>=1.10.0",
      "--with",
      "google-cloud-bigquery>=3.27.0",
      "--with",
      "google-cloud-build>=3.0.0",
      "--with",
      "google-cloud-compute>=1.0.0",
      "--with",
      "google-cloud-logging>=3.5.0",
      "--with",
      "google-cloud-monitoring>=2.0.0",
      "--with",
      "google-cloud-run>=0.9.0",
      "--with",
      "google-cloud-storage>=2.10.0",
      "--with",
      "mcp[cli]",
      "--with",
      "python-dotenv>=1.0.0",
      "mcp",
      "run",
      "C:\\Users\\enes_\\Desktop\\mcp-repo-final\\gcp-mcp\\src\\gcp-mcp-server\\main.py"
    ],
    "env": {
      "GOOGLE_APPLICATION_CREDENTIALS": "C:/Users/enes_/Desktop/mcp-repo-final/gcp-mcp/service-account.json",
      "GCP_PROJECT_ID": "gcp-mcp-cloud-project",
      "GCP_LOCATION": "us-east1"
    }
  }
}
Note: Your key is sensitive information, do not share it with anyone.
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