deploy_service_from_archive

SERVERGoogle Cloud Run SOURCEhttps://run.googleapis.com/mcp

High RISK CLASS

Category Execute

Parameters 11 required

Recommended Rate-limitedsee the rule below

Registry record Grade F, identity unverified Pull the record →

This record as markdown: /tools/com-googleapis-run-mcp/deploy-service-from-archive.md

WHAT IT DOES

What deploy_service_from_archive does on Google Cloud Run

AI agents invoke deploy_service_from_archive to trigger actions in Google Cloud Run. What it does depends on the arguments the agent supplies, and its effects often reach beyond the immediate call: builds kicked off, notifications sent, workflows started.

Parameter	Type	Required	Description
`service`	object	Yes	Required. The service to deploy.

Parameters from the server's own tool schema.

RISK

Why deploy_service_from_archive is rated High

deploy_service_from_archive triggers real processes with real consequences. An agent gone sideways doesn't fire it once. It starts dozens of builds, sends mass notifications, or burns through compute before anyone looks up.

Risk signalsAdmin/system-level operation

Attacks that exploit this kind of access

RECOMMENDED RULE

The rule that runs deploy_service_from_archive safely

PolicyLayer is an MCP gateway: it sits between your AI agents and Google Cloud Run, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For deploy_service_from_archive, this is the rule to start with:

deploy_service_from_archive Rate-limited

deploy_service_from_archive stays usable, but rate-capped: a runaway agent can't fire it dozens of times a minute. Everything else on the server is denied unless you say otherwise.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "deploy_service_from_archive": {
      "limits": [
        {
          "counter": "deploy_service_from_archive_rate",
          "window": "minute",
          "max": 10,
          "scope": "grant"
        }
      ]
    }
  }
}

RATE-LIMIT THIS TOOL → Instant setup, no code required.

The button opens the PolicyLayer dashboard: create your workspace, connect Google Cloud Run, apply this rule, and every deploy_service_from_archive call is checked against it from then on.

FAQ

Questions about deploy_service_from_archive

What does the deploy_service_from_archive tool do? +

Deploy a Cloud Run service directly from a self-contained source code archive (.tar.gz), skipping the container image build step for faster deployment. The archive must include all dependencies: - For compiled languages (Go, Java), include pre-compiled binaries. - For scripting languages (Python, Node.js), include pre-installed libraries (e.g., vendor/, node_modules/). Deployment steps: 1. Package source code and dependencies into a .tar.gz archive (max 250MiB). It's recommended to create archive from the root of the application's source directory. 2. Upload the archive to a Google Cloud Storage bucket, preferably in the same region as the service. 3. Deploy to Cloud Run using this tool, specifying: - source_code: Google Cloud Storage object path to the archive (e.g., gs://bucket/object). - command: Command to start the application. - base_image_uri: Base image for the container (e.g., go124, nodejs24, python314). See https://docs.cloud.google.com/run/docs/configuring/services/runtime-base-images for options. The runtime picked should match the local environment. - args: (Optional) Arguments for the command. - env: (Optional) Environment variables (e.g., name: PYTHONPATH, value: ./vendor). - ports: (Optional) Container ports to expose (defaults to 8080). It is categorised as a Execute tool in the Google Cloud Run MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.

What parameters does deploy_service_from_archive accept? +

deploy_service_from_archive accepts 1 parameter: service. Required: service. The full parameter table on this page comes from the server's own tool schema.

How do I enforce a policy on deploy_service_from_archive? +

Register the Google Cloud Run MCP server in PolicyLayer and add a rule for deploy_service_from_archive: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches Google Cloud Run. Nothing to install.

What risk level is deploy_service_from_archive? +

deploy_service_from_archive is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.

Can I rate-limit deploy_service_from_archive? +

Yes. Add a rate_limit block to the deploy_service_from_archive rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.

How do I block deploy_service_from_archive completely? +

Set action: deny in the PolicyLayer policy for deploy_service_from_archive. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.

What MCP server provides deploy_service_from_archive? +

deploy_service_from_archive is provided by the Google Cloud Run MCP server (https://run.googleapis.com/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

KEEP EXPLORING

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