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Google Cloud MCP Server: Scalable & Secure Model Management - MCP Implementation

Google Cloud MCP Server: Scalable & Secure Model Management

Google Cloud MCP Server: Scalable, secure model context management for AI at enterprise scale. Deploy fast, innovate faster.

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About Google Cloud MCP Server

What is Google Cloud MCP Server: Scalable & Secure Model Management?

Google Cloud MCP Server is a Model Context Protocol (MCP) service that integrates directly with core Google Cloud infrastructure. Designed for developers and DevOps engineers, it provides seamless access to critical Google Cloud resources like Logging, Monitoring, and Spanner. This server enables secure, scalable management of cloud assets while abstracting complex authentication and resource interaction logic.

How to use Google Cloud MCP Server: Scalable & Secure Model Management?

  1. Clone repository: git clone https://github.com/krzko/google-cloud-mcp.git
  2. Install dependencies with pnpm install
  3. Configure authentication via GOOGLE_APPLICATION_CREDENTIALS environment variable
  4. Launch server: pnpm start
  5. Integrate with clients using the provided configuration template

Google Cloud MCP Server Features

Key Features of Google Cloud MCP Server: Scalable & Secure Model Management?

  • Granular Resource Access: Query Logs, monitor metrics, and execute Spanner SQL queries through unified API
  • Lazy Authentication: Defer credential validation until first request to prevent startup timeouts
  • Mature & Emerging Support: Production-ready Logging/Monitoring/Spanner integrations with Trace/IAM/Compute in active development
  • Flexible Auth Options: Supports both service account files and direct environment variable injection

Use cases of Google Cloud MCP Server: Scalable & Secure Model Management?

  • Automated log correlation during incident response
  • Real-time performance dashboards using Monitoring metrics
  • Database schema exploration for Spanner deployments
  • Trace-based debugging of distributed systems
  • CI/CD pipeline integration for cloud resource validation

Google Cloud MCP Server FAQ

FAQ from Google Cloud MCP Server: Scalable & Secure Model Management?

Why use lazy authentication?
Avoids initialization delays caused by credential validation in large environments
How do I secure credentials?
Prefer service account files with restricted IAM permissions over environment variables for production deployments
What if I get 403 errors?
Verify service account has roles like Logging Viewer, Monitoring Viewer, and Spanner Data Viewer
Can I use this with Kubernetes?
Yes - mount credentials as secrets and configure env vars through deployment manifests
When will Trace/IAM support be ready?
Preview features expected Q3 2024 - sign up for beta access via GitHub issues

Content

Google Cloud MCP Server

A Model Context Protocol server that connects to Google Cloud services to provide context and tools for interacting with your Google Cloud resources.

Services

Supported services:

  • Google Cloud Logging
  • Google Cloud Monitoring
  • Google Cloud Spanner

Servers in development:

  • Google Cloud Trace
  • Google IAM
  • Google Cloud Compute
  • Google Cloud Run
  • Google Cloud Storage

Google Cloud Logging

Query and filter log entries from Google Cloud Logging:

  • Query logs with custom filters
  • Search logs within specific time ranges
  • Format and display log entries in a readable format

Google Cloud Spanner

Interact with Google Cloud Spanner databases:

  • Execute SQL queries against Spanner databases
  • List available databases and tables
  • Explore database schema

Google Cloud Monitoring

Retrieve and analyse metrics from Google Cloud Monitoring:

  • Query metrics with custom filters
  • Visualise metric data over time
  • List available metric types

Google Cloud Trace

Analyse distributed traces from Google Cloud Trace:

  • Retrieve traces by ID
  • List recent traces with filtering options
  • Find traces associated with logs
  • Identify failed traces
  • Use natural language to query traces (e.g., "Show me failed traces from the last hour")

Authentication

This server supports two methods of authentication with Google Cloud:

  1. Service Account Key File (Recommended): Set the GOOGLE_APPLICATION_CREDENTIALS environment variable to the path of your service account key file. This is the standard Google Cloud authentication method.

  2. Environment Variables : Set GOOGLE_CLIENT_EMAIL and GOOGLE_PRIVATE_KEY environment variables directly. This is useful for environments where storing a key file is not practical.

The server will also use the GOOGLE_CLOUD_PROJECT environment variable if set, otherwise it will attempt to determine the project ID from the authentication credentials.

Installation

# Clone the repository
git clone https://github.com/krzko/google-cloud-mcp.git
cd google-cloud-mcp

# Install dependencies
pnpm install

# Build
pnpm build

Authenticate to Google Cloud:

gcloud auth application-default login

Configure the mcpServers in your client:

{
  "mcpServers": {
      "google-cloud-mcp": {
          "command": "node",
          "args": [
              "/Users/foo/code/google-cloud-mcp/dist/index.js"
          ],
          "env": {
              "GOOGLE_APPLICATION_CREDENTIALS": "/Users/foo/.config/gcloud/application_default_credentials.json"
          }
      }
  }
}

Development

Starting the server

# Build the project
pnpm build

# Start the server
pnpm start

Development mode

# Build the project
pnpm build

# Start the server and inspector
npx -y @modelcontextprotocol/inspector node dist/index.js

Using with Smithery (soon)

This server can be deployed and used with Smithery. The server implements lazy loading of authentication, which means it will start immediately and defer authentication until it's actually needed. Authentication is still required for operation, but this approach prevents timeouts during server initialization.

NOTE: Smithery local server support is currently in development and may not yet available.

Troubleshooting

Server Timeout Issues

If you encounter timeout issues when running the server with Smithery, try the following:

  1. Enable debug logging by setting debug: true in your configuration
  2. Ensure lazyAuth: true is set to defer authentication until it's actually needed
  3. Ensure your credentials file is accessible and valid
  4. Check the logs for any error messages

Important : Authentication is still required for operation, but with lazy loading enabled, the server will start immediately and authenticate when needed rather than during initialization.

Authentication Issues

The server supports two methods of authentication:

  1. Service Account Key File : Set GOOGLE_APPLICATION_CREDENTIALS environment variable to the path of your service account key file
  2. Environment Variables : Set GOOGLE_CLIENT_EMAIL and GOOGLE_PRIVATE_KEY environment variables

If you're having authentication issues, make sure:

  • Your service account has the necessary permissions
  • The key file is properly formatted and accessible
  • Environment variables are correctly set

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