Claude-skill-registry Cloud Run Manager

Tool suite for deploying and managing Google Cloud Run services. Use for deployments, logging, and service inspection.

install
source · Clone the upstream repo
git clone https://github.com/majiayu000/claude-skill-registry
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/majiayu000/claude-skill-registry "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/data/cloud-run-manager" ~/.claude/skills/majiayu000-claude-skill-registry-cloud-run-manager-63e68b && rm -rf "$T"
manifest: skills/data/cloud-run-manager/SKILL.md
source content

Cloud Run Manager Skill

This skill grants access to the Google Cloud Run MCP tools. Use this to manage the lifecycle of containerized applications.

When to use

  • Deploying new services (source or container based).
  • Inspecting running services.
  • Fetching service logs for debugging.
  • Listing projects and services.

Available Tools (Context Loaded)

The following tools are available via the

cloudrun
MCP server:

Deployment

  • mcp_cloudrun_create_project
    : Initialize a new GCP project.
  • mcp_cloudrun_deploy_container_image
    : Deploy an existing image (e.g., from GCR/Artifact Registry).
  • mcp_cloudrun_deploy_local_folder
    : Deploy source code directly from a local path.
  • mcp_cloudrun_deploy_file_contents
    : Deploy ad-hoc files (useful for quick tests).

Management & Observability

  • mcp_cloudrun_list_projects
    : View available GCP projects.
  • mcp_cloudrun_list_services
    : List services in a project.
  • mcp_cloudrun_get_service
    : Get detailed status/config of a generic service.
  • mcp_cloudrun_get_service_log
    : Retrieve logs and error messages.

Best Practices

  1. Project ID: Always confirm the
    project
    ID with the user or via
    list_projects
    before deploying.
  2. Region: Default to
    us-central1
    if unspecified, or ask the user.
  3. Logs: usage of
    get_service_log
    is expensive; request specific timeframes or limits if possible.

Example Workflow

  1. User: "Deploy this folder to Cloud Run."
  2. Agent: Calls
    mcp_cloudrun_list_projects
    to verify destination.
  3. Agent: Calls
    mcp_cloudrun_deploy_local_folder
    .