gcp_compute_set_labels

Set labels on a VM instance

SERVERGCP MCP Server SOURCEahmedselimmansor-ctrl/gcp_mcp_server

Medium RISK CLASS

Category Write

Parameters 00 required

Recommended Rate-limitedsee the rule below

Registry record Grade F, identity unverified Pull the record →

This record as markdown: /tools/ahmedselimmansor-ctrl-gcp-mcp-server/gcp-compute-set-labels.md

WHAT IT DOES

What gcp_compute_set_labels does on GCP MCP Server

AI agents use gcp_compute_set_labels to create or update resources in GCP MCP Server, usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your GCP MCP Server environment.

RISK

Why gcp_compute_set_labels is rated Medium

Setting labels on a VM instance is a write operation that modifies resource metadata. This is reversible (labels can be changed or removed), affects only configuration metadata rather than core infrastructure or data, and does not involve deletion, financial transactions, or direct code/command execution.

From the tool's definition Tool name 'gcp_compute_set_labels' and description 'Set labels on a VM instance' indicate a metadata modification operation. Labels are attributes applied to GCP resources that are reversible and do not directly affect the VM's core functionality or data.

Attacks that exploit this kind of access

RECOMMENDED RULE

The rule that runs gcp_compute_set_labels safely

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

gcp_compute_set_labels Rate-limited

gcp_compute_set_labels stays usable, but capped: an agent stuck in a loop can't make hundreds of changes a minute. Everything else on the server is denied unless you say otherwise.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "gcp_compute_set_labels": {
      "limits": [
        {
          "counter": "gcp_compute_set_labels_rate",
          "window": "minute",
          "max": 30,
          "scope": "grant"
        }
      ]
    }
  }
}

LIMIT THIS TOOL → Instant setup, no code required.

The button opens the PolicyLayer dashboard: create your workspace, connect GCP MCP Server, apply this rule, and every gcp_compute_set_labels call is checked against it from then on.

FAQ

Questions about gcp_compute_set_labels

What does the gcp_compute_set_labels tool do? +

Set labels on a VM instance. It is categorised as a Write tool in the GCP MCP Server MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on gcp_compute_set_labels? +

Register the GCP MCP Server MCP server in PolicyLayer and add a rule for gcp_compute_set_labels: 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 GCP MCP Server. Nothing to install.

What risk level is gcp_compute_set_labels? +

gcp_compute_set_labels is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.

Can I rate-limit gcp_compute_set_labels? +

Yes. Add a rate_limit block to the gcp_compute_set_labels 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 gcp_compute_set_labels completely? +

Set action: deny in the PolicyLayer policy for gcp_compute_set_labels. 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 gcp_compute_set_labels? +

gcp_compute_set_labels is provided by the GCP MCP Server MCP server (ahmedselimmansor-ctrl/gcp_mcp_server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

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