grok-mcp-cloudrun

grok-mcp-cloudrun

Grok plugin for deploying and managing Google Cloud Run services via MCP tools, slash commands, and a skill.

Category
Visit Server

README

grok-mcp-cloudrun

Grok plugin for deploying and managing Google Cloud Run services.

Deploy and manage Cloud Run from Grok using MCP tools, slash commands, and a Cloud Run skill. This repo is a thin wrapper around Google's open-source @google-cloud/cloud-run-mcp — it does not fork or vendor the upstream server.

Not affiliated with Google. See NOTICE for upstream attribution.

See GROK-CHANGES.md for a full list of Grok-specific additions and lessons learned from testing.


Table of contents

  1. What you get
  2. Prerequisites
  3. Quick start
  4. Installation
  5. Quick test (deploy + curl)
  6. Daily usage
  7. Configuration reference
  8. Troubleshooting
  9. Project layout
  10. Hosted MCP vs local plugin
  11. License

What you get

Component What it does
MCP server Deploy folders, list services, fetch logs via cloud-run__* tools
Skill cloud-run — MCP-first workflow with gcloud fallback
Slash commands /deploy and /logs
Hooks Warns if no GCP project is set; blocks create-project by default

Prerequisites

Install and authenticate before anything else.

1. Google Cloud SDK

gcloud auth login
gcloud auth application-default login
gcloud config set project YOUR_PROJECT_ID

2. Environment variables

export GOOGLE_CLOUD_PROJECT=YOUR_PROJECT_ID
export GOOGLE_CLOUD_REGION=us-central1          # optional, defaults to us-central1
export DEFAULT_SERVICE_NAME=                    # optional, defaults to cwd basename

3. Node.js

Node.js LTS is required for npx to spawn the MCP server.

4. IAM roles

Your account needs permission to deploy and read Cloud Run resources:

Action Minimum roles
Deploy roles/run.admin — or roles/run.developer + roles/iam.serviceAccountUser
Logs roles/logging.viewer + Cloud Run read access
Source upload roles/storage.admin, roles/artifactregistry.writer (as needed by your build)

5. Verify MCP connectivity

grok mcp doctor cloud-run

Expected output: Found 1 healthy, 0 failing with 8 tools discovered.


Quick start

If this repo is already on your machine:

# Install and trust the plugin
grok plugin install /path/to/grok-mcp-cloudrun --trust
grok plugin enable cloud-run

# Confirm everything loaded
grok plugin validate /path/to/grok-mcp-cloudrun
grok inspect

Open Grok and check:

  • /pluginscloud-run is enabled
  • /mcpscloud-run server shows 8 tools
  • /skillscloud-run skill is listed

Installation

Choose one path. Do not enable both with the same server name — pick plugin or bare MCP config.

Option A: Plugin (recommended)

Includes skills, slash commands, and safety hooks.

grok plugin install /path/to/grok-mcp-cloudrun --trust
grok plugin enable cloud-run

The --trust flag is required for MCP servers and hooks to activate.

Option B: MCP config only

For personal use without the plugin wrapper:

grok mcp add cloud-run \
  -e GOOGLE_CLOUD_PROJECT=YOUR_PROJECT_ID \
  -e GOOGLE_CLOUD_REGION=us-central1 \
  -- npx -y @google-cloud/cloud-run-mcp@1.10.0

Or add manually to ~/.grok/config.toml:

[mcp_servers.cloud-run]
command = "npx"
args = ["-y", "@google-cloud/cloud-run-mcp@1.10.0"]
enabled = true
startup_timeout_sec = 60

[mcp_servers.cloud-run.env]
GOOGLE_CLOUD_PROJECT = "${GOOGLE_CLOUD_PROJECT}"
GOOGLE_CLOUD_REGION  = "${GOOGLE_CLOUD_REGION:-us-central1}"
DEFAULT_SERVICE_NAME = "${DEFAULT_SERVICE_NAME:-}"

[mcp_servers.cloud-run.tool_timeouts]
deploy-local-folder = 600

Quick test (deploy + curl)

End-to-end smoke test: clone a sample app, deploy it from Grok, then hit it with curl.

Step 1 — Clone the sample

git clone https://github.com/GoogleCloudPlatform/cloud-run-mcp.git /tmp/cloud-run-mcp
cd /tmp/cloud-run-mcp/example-sources-to-deploy/nodejs

Upstream also provides golang, java, and python samples in the same directory.

Step 2 — Deploy from Grok

In a Grok session (with this directory as your working folder):

/deploy hello-test

Grok calls cloud-run__deploy-local-folder and returns a public HTTPS URL when the deploy finishes. First deploy can take several minutes (Cloud Build + container push).

Step 3 — Verify with curl

Use the URL from the deploy response, or look it up with gcloud:

# Option A: URL from /deploy output
curl -sS https://hello-test-XXXXXXXX-uc.a.run.app/

# Option B: resolve URL via gcloud
SERVICE_URL=$(gcloud run services describe hello-test \
  --region="${GOOGLE_CLOUD_REGION:-us-central1}" \
  --project="${GOOGLE_CLOUD_PROJECT}" \
  --format='value(status.url)')

curl -sS "$SERVICE_URL/"

Expected response:

Hello from Node.js on Cloud Run!

Health check:

curl -sS -o /dev/null -w "HTTP %{http_code}\n" "$SERVICE_URL/health"

Expected: HTTP 200

Step 4 — Check logs

Back in Grok:

/logs hello-test

Or from the shell:

gcloud run services logs read hello-test \
  --region="${GOOGLE_CLOUD_REGION:-us-central1}" \
  --limit=20

Step 5 — Clean up (optional)

gcloud run services delete hello-test \
  --region="${GOOGLE_CLOUD_REGION:-us-central1}" \
  --quiet

Daily usage

Slash commands

Command Action
/deploy Deploy cwd; service name = directory basename
/deploy my-api Deploy cwd as my-api
/logs Logs for default service name
/logs my-api Logs for my-api

Natural language prompts

  • "List Cloud Run services in my-project region us-central1"
  • "Deploy the current folder to Cloud Run"
  • "Get the URL for service hello-test"
  • "Show me recent errors in Cloud Run logs for my-api"

MCP tools

Grok namespaces tools as cloud-run__<tool>:

Tool Purpose
cloud-run__deploy-local-folder Deploy cwd to Cloud Run
cloud-run__deploy-file-contents Deploy files by content (remote mode)
cloud-run__list-services List services in project/region
cloud-run__get-service Service details and public URL
cloud-run__get-service-log Recent logs and errors
cloud-run__list-projects List GCP projects
cloud-run__create-project Create project (blocked by default hook)

Discover tools at runtime with search_tool, then call with use_tool.


Configuration reference

Environment variables

Variable Default Description
GOOGLE_CLOUD_PROJECT GCP project for all operations
GOOGLE_CLOUD_REGION us-central1 Cloud Run region
DEFAULT_SERVICE_NAME cwd basename Default name for /deploy and /logs
SKIP_IAM_CHECK true (upstream) When true, new services may be publicly accessible
CONFIRM_CLOUD_RUN_CREATE_PROJECT unset Set to 1 to allow create-project (hook blocks it otherwise)
CONFIRM_CLOUD_RUN_PROD_DEPLOY unset Set to 1 to deploy when project ID looks like production

Safety hooks

The plugin ships hooks/hooks.json:

  • SessionStart — warns if neither GOOGLE_CLOUD_PROJECT nor a gcloud default project is set; warns if ADC is missing
  • PreToolUse — blocks cloud-run__create-project unless CONFIRM_CLOUD_RUN_CREATE_PROJECT=1
  • PreToolUse — blocks deploy tools to production-like projects unless CONFIRM_CLOUD_RUN_PROD_DEPLOY=1

Timeouts

Cold npx downloads can exceed the default 30s startup timeout. This repo's config uses:

  • startup_timeout_sec = 60
  • tool_timeouts.deploy-local-folder = 600 (10 min for first deploy)

Troubleshooting

Symptom Fix
grok mcp doctor cloud-run fails gcloud auth application-default login
MCP starts but deploy fails with auth error Re-run ADC login; confirm GOOGLE_CLOUD_PROJECT
Cold start / connection timeout Set startup_timeout_sec = 60 in config
Deploy hangs or times out Set tool_timeouts = { deploy-local-folder = 600 }
Permission denied on deploy Check IAM roles in Prerequisites
Plugin MCP shows blocked Reinstall with grok plugin install ... --trust
Plugin installed but tools missing grok plugin enable cloud-run
curl returns 403 Service may not be public; check IAM or set SKIP_IAM_CHECK=false and add allUsers invoker binding
curl connection refused right after deploy Wait 30–60s for the new revision to become ready, then retry

Diagnostic commands

./scripts/verify-setup.sh          # full Phase 3 checklist
grok mcp doctor cloud-run          # MCP health
grok plugin validate .             # plugin manifest
grok inspect                       # skills, commands, hooks, MCP inventory
grok plugin list                   # installed plugins
gcloud auth application-default print-access-token  # confirm ADC

Marketplace

Install from GitHub:

grok plugin install gprot42/grok-mcp-cloudrun --trust
grok plugin enable cloud-run

To submit to the official xAI marketplace, see MARKETPLACE.md.


Project layout

grok-mcp-cloudrun/
├── .mcp.json                  # MCP server config (Grok primary)
├── .claude-plugin/plugin.json # Claude-ecosystem compat
├── .grok-plugin/plugin.json   # Marketplace manifest
├── plugin.json                # Plugin metadata
├── commands/
│   ├── deploy.md              # /deploy slash command
│   └── logs.md                # /logs slash command
├── hooks/hooks.json           # SessionStart + PreToolUse safety
├── skills/cloud-run/SKILL.md  # MCP-first Cloud Run workflow
├── LICENSE                    # Apache 2.0 (upstream)
├── NOTICE                     # Upstream attribution
└── README.md                  # This guide

Hosted MCP vs local plugin

This plugin runs the MCP server locally via stdio (npx @google-cloud/cloud-run-mcp). That is what powers /deploy, which calls cloud-run__deploy-local-folder on your current working directory.

If you deploy the upstream MCP server itself to Cloud Run, it behaves differently:

Local plugin (this repo) Hosted on Cloud Run
Transport stdio via npx POST /mcp or GET /sse
/deploy (local folder) Works Not available
Deploy by file contents Yes Yes
Browser at service URL N/A Cannot GET / (expected — no web UI)

To verify a hosted MCP deployment, send an MCP initialize request to /mcp (see GROK-CHANGES.md).

For Grok day-to-day use, install this plugin — do not point Grok at a public Cloud Run URL without IAM authentication.


License

Apache License 2.0. See LICENSE and NOTICE.

Upstream MCP server: GoogleCloudPlatform/cloud-run-mcp · npm: @google-cloud/cloud-run-mcp@1.10.0

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured