What is Cloud Run Mcp

cloud-run-mcp is an MCP server designed to deploy applications to Google Cloud Run, enabling seamless integration with AI agents for deployment tasks.

Use cases

Use cases include deploying applications from AI-powered IDEs, integrating with AI assistant apps, and utilizing agent SDKs for streamlined deployment processes.

How to use

To use cloud-run-mcp, install Node.js and the Google Cloud SDK, authenticate your Google account, and then run commands to deploy applications or manage Cloud Run services using the provided tools.

Key features

Key features include the ability to deploy files directly, list and get details of Cloud Run services, and manage Google Cloud projects, with local deployment options available for enhanced flexibility.

Where to use

cloud-run-mcp can be used in various fields such as software development, cloud computing, and AI applications, particularly where deployment automation is beneficial.

MCP server to deploy code to Google Cloud Run

Enable MCP-compatible AI agents to deploy apps to Cloud Run.

Deploy from AI-powered IDEs:

Deploy from AI assistant apps:

Deploy from agent SDKs, like the Google Gen AI SDK or Agent Development Kit.

[!NOTE]
This is the repository of an MCP server to deploy code to Cloud Run, to learn how to host MCP servers on Cloud Run, visit the Cloud Run documentation.

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-files*: Deploys files from the local file system to a Google 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. A project ID can be optionally specified.

* only available when running locally

Use as local MCP server

Run the Cloud Run MCP server on your local machine using local Google Cloud credentials. This is best if you are using an AI-assisted IDE (e.g. Cursor) or a desktop AI application (e.g. Claude).

0. Install Node.js (LTS version recommended).

1. Install the Google Cloud SDK and authenticate with your Google account.

2. Log in to your Google Cloud account using the command:

   gcloud auth login
   

3. Set up application credentials using the command:

   gcloud auth application-default login
   

4. Update the MCP configuration file of your MCP client with the following:

Use as remote MCP server

[!WARNING]
Do not use the remote MCP server without authentication. In the following instructions, we will use IAM authentication to secure the connection to the MCP server from your local machine. This is important to prevent unauthorized access to your Google Cloud resources.

Run the Cloud Run MCP server itself on Cloud Run with connection from your local machine authenticated via IAM.
With this option, you will only be able to deploy code to the same Google Cloud project as where the MCP server is running.

1. Install the Google Cloud SDK and authenticate with your Google account.

2. Log in to your Google Cloud account using the command:

   gcloud auth login
   

3. Set your Google Cloud project ID using the command:

   gcloud config set project YOUR_PROJECT_ID
   

4. Deploy the Cloud Run MCP server to Cloud Run:

   gcloud run deploy cloud-run-mcp --image us-docker.pkg.dev/cloudrun/container/mcp --no-allow-unauthenticated
   

   When prompted, pick a region, for example europe-west1.

   Note that the MCP server is not publicly accessible, it requires authentication via IAM.

5. Run a Cloud Run proxy on your local machine to connect securely using your identity to the remote MCP server running on Cloud Run:

   gcloud run services proxy cloud-run-mcp --port=3000 --region=REGION --project=PROJECT_ID
   

   This will create a local proxy on port 3000 that forwards requests to the remote MCP server and injects your identity.

6. Update the MCP configuration file of your MCP client with the following:

   If your MCP client does not support the url attribute, you can use mcp-remote: