wehub-resource-sync
44 lines
1.9 KiB
Markdown
44 lines
1.9 KiB
Markdown
# Cloud Run MCP Usage
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Cloud Run is supported by a remote Model Context Protocol (MCP) server that
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enables agents to deploy, manage, and monitor serverless applications.
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## MCP Tools for Cloud Run
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The Cloud Run MCP server typically includes tools for:
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- `get_service`: Get info about a Cloud Run service, such as its URI and
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whether the deploy succeeded.
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- `list_services`: List Cloud Run services in a given Google Cloud project and
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region.
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- `deploy_service_from_image`: Deploy a container image from Artifact Registry
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or Docker Hub as a Cloud Run service.
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- `deploy_service_from_archive`: Deploy a Cloud Run service directly from a
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self-contained source code archive (.tar.gz), skipping the container image
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build step for faster deployment. The archive must include all dependencies.
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- `deploy_service_from_file_contents`: Deploys a Cloud Run service directly from
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local source files. This method is suitable for scripting languages like Python
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and Node.js, of which the source code can be embedded in the request. This is
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ideal for quick tests and development feedback loops. You must include all
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necessary dependencies within the source files because it skips the build step
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for faster deployment.
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## Setup Instructions
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To connect to the Cloud Run MCP server:
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1. Enable the Cloud Run API in your Google Cloud project.
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2. Configure the agent's MCP connection using the Gemini CLI extension.
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3. Follow the setup guide:
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[Setting up Cloud Run MCP](https://docs.cloud.google.com/run/docs/reference/mcp).
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## Supported Operations
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Agents using the Cloud Run MCP can:
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- Automate the rollout of new revisions.
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- Troubleshoot failing deployments by inspecting logs and status.
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- Manage scheduled jobs and verify their execution history.
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Alternatively, use the [open source Cloud Run MCP server](https://github.com/GoogleCloudPlatform/cloud-run-mcp) which runs locally.
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