Best for
- Developers and teams wanting to integrate deployment into AI workflows
- Users already using Google Cloud and Cloud Run
- AI agents that need to quickly prototype or deploy applications
C
47FMRS · D
A powerful MCP server for Cloud Run deployment, offering a variety of tools and prompts. It is great for AI-assisted workflows but requires careful configuration of authentication and security settings.
The Cloud Run MCP server enables MCP-compatible AI agents to deploy apps to Google Cloud Run. It provides tools to deploy files or local folders, list and manage services, and fetch logs. Additionally, it includes prompts for common tasks, and advanced tools for project management.
Tools
deploy-file-contents
Deploys files to Cloud Run by providing their contents directly.
list-services
Lists Cloud Run services in a given project and region.
get-service
Gets details for a specific Cloud Run service.
get-service-log
Gets Logs and Error Messages for a specific Cloud Run service.
deploy-local-folder
Deploys a local folder to a Google Cloud Run service.
list-projects
Lists available GCP projects.
create-project
Creates a new GCP project and attach it to the first available billing account.
Setup
- Install Google Cloud SDK and authenticate:
gcloud auth loginandgcloud auth application-default login. - Configure MCP client with npx command:
npx -y @google-cloud/cloud-run-mcp. - Optionally set environment variables like
GOOGLE_CLOUD_PROJECT,GOOGLE_CLOUD_REGION, andDEFAULT_SERVICE_NAME.
claude_desktop_config.json
{
"mcpServers": {
"cloud-run": {
"command": "npx",
"args": [
"-y",
"@google-cloud/cloud-run-mcp"
]
}
}
}
Fit and risk
Not for
- Deployments requiring local hosting or other cloud provider support
- Users wanting fine-grained IAM control without skipping permission checks
- Seeking GitOps or fully automated CI/CD without MCP/CLI
Required permissions
- Requires Google Cloud IAM credentials to access Cloud Run APIs.
- Authentication via `gcloud auth login` and `gcloud auth application-default login`.
- Deployment requires appropriate Cloud Run permissions like `run.services.create` and `run.services.update`.
- Project creation requires permissions like `resourcemanager.projects.create`.
Risks and side effects
- Using remote MCP server without authentication may lead to unauthorized access.
- IAM checks are skipped by default (`SKIP_IAM_CHECK=true`), potentially allowing overly permissive access.
- Deploying file contents may expose sensitive data if provided in prompts.
- DNS rebinding risk unless host validation is enabled (`ENABLE_HOST_VALIDATION`).
Troubleshooting
- Ensure gcloud is installed and authenticated properly.
- Verify default project and region settings.
- Check `SKIP_IAM_CHECK` setting if encountering permission errors.
- For remote setup, ensure the Cloud Run MCP server is deployed in the same project.
- If connection issues, run `gcloud auth application-default login`.
Use cases
Deploy applications from AI-assisted IDEs (e.g., Cursor) or desktop AI apps (e.g., Claude)
AI-agent-driven deployment via Gemini CLI or agent SDKs
Automate Cloud Run service management in cloud environments
Supported clients
Gemini CLIFull support
Claude DesktopPartial support
VSCodePartial support
CursorPartial support
WindsurfPartial support
AntigravityPartial support