Use this as the primary tool to list the alerting policies in a Google Cloud project. Alerting policies define the conditions under which you want to be notified about issues with your services. This is useful for understanding what alerts are currently configured.
AI agents call list_alert_policies to retrieve information from Storage without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool queries and retrieves alert policy configuration data from Google Cloud without modifying, deleting, or executing any changes. It is a read-only operation that returns existing state information, making it fall squarely in the Read category with low severity since misuse would only expose existing alerting configuration.
From the tool's definition Tool name contains 'list' and description explicitly states 'list the alerting policies' with purpose of 'understanding what alerts are currently configured' — a pure information retrieval operation with no side effects.
Attacks that exploit this kind of access
Use this as the primary tool to list the alerting policies in a Google Cloud project. Alerting policies define the conditions under which you want to be notified about issues with your services. This is useful for understanding what alerts are currently configured. It is categorised as a Read tool in the Storage MCP Server, which means it retrieves data without modifying state.
Register the Storage MCP server in PolicyLayer and add a rule for list_alert_policies: 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 Storage. Nothing to install.
list_alert_policies is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the list_alert_policies 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 list_alert_policies. 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.
list_alert_policies is provided by the Storage MCP server (@google-cloud/storage-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.