AI agents use select-project to create or update resources in GCP MCP — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your GCP MCP environment.
While the tool does not create, modify, or delete actual GCP resources, it alters the execution context for subsequent interactions. This is a reversible state change (another project can be selected afterward), making it Write rather than Read or Execute.
From the tool's definition Tool performs 'selects GCP project' which modifies the state of subsequent operations by changing which project context is active.
Attacks that exploit this kind of access
Selects GCP project to use for subsequent interactions. It is categorised as a Write tool in the GCP MCP MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the GCP MCP server in PolicyLayer and add a rule for select-project: 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. Nothing to install.
select-project is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.
Yes. Add a rate_limit block to the select-project 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.
Set action: deny in the PolicyLayer policy for select-project. 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.
select-project is provided by the GCP MCP server (radiumgu/gcp-ops-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Every MCP server has a record like this.
Type a name, get the same breakdown: verified identity, auth posture, risk grade, capabilities, recommended policy.
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