MCP server
Google Cloud MCP server
Google's gcloud MCP servers let AI run gcloud commands, read logs, metrics, alerts and traces, and work with Cloud Storage.
- Official server
- Cloud and infrastructure
At a glance
- Maintained by
- Google (googleapis GitHub org)
- Tools exposed
- 9 listed below
- Reviewed
- September 24, 2026
Why it matters
What it does and why it matters
Google publishes a set of MCP servers for Google Cloud in its googleapis organization. The main one runs gcloud commands, which covers most Google Cloud services. Related servers in the same repository read logs, metrics, alert policies and traces, and list, read and write Cloud Storage objects.
For teams on Google Cloud, that means one assistant can check a service, read its logs and look at related metrics in one conversation.
The repository states that it is not an officially supported Google product, even though it is published by Google. Treat it with the same care as a community tool. The gcloud tool can change most resources your account can touch, so use a service account with narrow roles and keep production changes behind review.
Use cases
Best business use cases
Log questions
Metrics
Alerts
Storage
gcloud help
Tools
Available tools
Tool names as published by the maintainer at review time. Versions change, so check the repository for the current list.
Main server is gcloud, which has one tool. Other tools come from the observability and storage servers in the same repo; each is installed as its own package.
Read and write: Read and write: gcloud can change most resources your account can touch; observability tools are read-only; storage tools read and write.
-
run_gcloud_commandgcloud server. Run a gcloud CLI command; unsafe or interactive commands are blocked.
-
list_log_entriesobservability server. List log entries for a project.
-
list_time_seriesobservability server. List time series data for a metric.
-
list_alert_policiesobservability server. List alert policies in a project.
-
list_tracesobservability server. Search traces in a project.
-
list_objectsstorage server. List objects in a Cloud Storage bucket.
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read_object_contentstorage server. Read the content of an object.
-
write_objectstorage server. Write a new object to a bucket.
-
create_bucketstorage server. Create a new bucket.
Workflows
Example workflows
Trace an error
-
1
Describe the error.
-
2
The assistant reads recent log entries.
-
3
It checks related traces.
-
4
It explains the likely cause.
-
5
An engineer applies the fix.
Review alerting
-
1
Ask for alert policies.
-
2
The assistant lists them.
-
3
It notes services without alerts.
-
4
It suggests new alerts.
-
5
The team decides which to add.
Prompts
Example prompts
“Show error logs for the checkout service in the last hour.”
“Which services have no alert policy?”
“List objects uploaded to the exports bucket today.”
Setup
Installation and configuration
Examples for Claude Desktop and Claude Code. Replace the placeholder values with your own keys, and store secrets outside version control.
Claude Desktop: claude_desktop_config.json
{
"mcpServers": {
"gcloud": {
"command": "npx",
"args": [
"-y",
"@google-cloud/gcloud-mcp"
]
}
}
}Claude Code: terminal
claude mcp add gcloud -- npx -y @google-cloud/gcloud-mcp- Local server: npm: @google-cloud/gcloud-mcp (stdio). Same repo also ships @google-cloud/observability-mcp, @google-cloud/storage-mcp and @google-cloud/backupdr-mcp..
- Needs: Uses the active gcloud CLI account (gcloud auth login). Service account impersonation supported. Node.js 20+ required..
Security
Security considerations
-
Read-only first
Start with read access and add actions only for reviewed tasks.
-
Scoped credentials
Use a dedicated role or token with the least access, never an owner or admin key.
-
Separate environments
Keep production changes out of assistant sessions, or require approval for them.
-
Audit
Use Cloud Audit Logs to review actions.
Related servers
Servers that pair well with it
BigQuery
Google's remote BigQuery MCP server lets AI list datasets and tables and run SQL, with a read-only query tool and IAM controls.
AWS
The AWS API MCP server from AWS Labs lets AI run AWS CLI commands, suggest commands and plan changes, with read-only and consent modes.
Azure
Microsoft's Azure MCP server lets AI work with many Azure services, from storage and Key Vault to SQL, monitoring and AKS, with a read-only mode.
Keep exploring
Solutions and services that use it
Related services
View all related services- MCP integration Connect AI assistants to your CRM, files, databases and tools through Model Context Protocol servers, with safe permissions.
- Product scaling Keep a growing product fast and stable as users, data and features increase.
- Multi-tenant architecture One product serving many customer accounts, with each account's data kept separate and secure.
- API integration Make two systems share data reliably, with retries, logging and alerts when something goes wrong.
- AI-Powered Web Development Business websites, customer portals, dashboards and web applications that load fast, rank well and are easy to change.
- Automation and Integrations CRM, payment and API integrations, MCP connections and workflows that stop people copying data by hand.
Solutions
View all solutionsIndustries
View all industriesGuides and articles
View all guides and articles- How we review AI-generated code The checks we apply to every AI-assisted change, from tests and security to readability and business rules.
- How to connect AI to your database safely Let staff ask questions of your data in plain English without risking production systems or sensitive records.
- MCP security best practices How to choose, configure and monitor MCP servers so AI assistants get the access they need and nothing more.
- How to automate reporting with AI and MCP Build reports that assemble themselves from your systems through MCP, with a written summary people can trust.
- How to set up automated reporting Replace manual weekly and monthly reports with dashboards and summaries that update themselves.
Glossary terms
View all glossary terms- API integration An API integration connects two or more systems through their APIs so data and actions flow between them automatically.
- Machine learning Machine learning is a way of building software that learns patterns from data to make predictions or decisions, instead of following only hand-written rules.
- Cloud hosting Cloud hosting runs websites and applications on servers rented from a provider, which can grow or shrink with demand.
- Reverse proxy A reverse proxy is a server that sits in front of your applications, receiving visitors' requests and passing them to the right app, often adding security and caching.
- VPS A VPS, or virtual private server, is a rented virtual machine with its own resources, on which you can install and run your own software.
- API An API, or application programming interface, is a defined way for one piece of software to request data or actions from another.
FAQ
Questions people ask us
Have a question that is not here? Ask us directly.
It is published by Google, but its repository says it is not an officially supported Google product.
Run gcloud commands, read observability data and work with Cloud Storage.
Yes. Google hosts a remote BigQuery MCP server.