gcp_agent_get_model

Get details of a Vertex AI model

SERVERGCP MCP Server SOURCEahmedselimmansor-ctrl/gcp_mcp_server

Low RISK CLASS

Category Read

Parameters 00 required

Recommended Allowedsee the rule below

Registry record Grade F, identity unverified Pull the record →

This record as markdown: /tools/ahmedselimmansor-ctrl-gcp-mcp-server/gcp-agent-get-model.md

WHAT IT DOES

What gcp_agent_get_model does on GCP MCP Server

AI agents call gcp_agent_get_model to retrieve information from GCP MCP Server without modifying anything. It is typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.

RISK

Why gcp_agent_get_model is rated Low

This tool retrieves metadata and details about an existing Vertex AI model. It performs a query-only operation without creating, modifying, deleting, or executing any actions. The 'get' operation is a read-only accessor that returns information about a resource. Severity is low as the blast radius of misuse is limited to potential information disclosure of model metadata.

From the tool's definition Tool name 'get_model' and description 'Get details of a Vertex AI model' indicate a retrieval operation with no modification or side effects.

Attacks that exploit this kind of access

RECOMMENDED RULE

The rule that runs gcp_agent_get_model 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_agent_get_model, this is the rule to start with:

gcp_agent_get_model Allowed

gcp_agent_get_model is read-only, so it stays allowed. Everything else on the server is denied unless you say otherwise.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "gcp_agent_get_model": {}
  }
}

ALLOW ONLY 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_agent_get_model call is checked against it from then on.

FAQ

Questions about gcp_agent_get_model

What does the gcp_agent_get_model tool do? +

Get details of a Vertex AI model. It is categorised as a Read tool in the GCP MCP Server MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on gcp_agent_get_model? +

Register the GCP MCP Server MCP server in PolicyLayer and add a rule for gcp_agent_get_model: 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_agent_get_model? +

gcp_agent_get_model is a Read tool with low risk. Read-only tools are generally safe to allow by default.

Can I rate-limit gcp_agent_get_model? +

Yes. Add a rate_limit block to the gcp_agent_get_model 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_agent_get_model completely? +

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

gcp_agent_get_model 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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