AI agents call list_gmail_labels to retrieve information from Gg without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool queries and returns existing Gmail label data without creating, modifying, or deleting anything. It is a straightforward read operation with minimal security risk—it only exposes metadata about label organization that the authenticated user already has access to.
From the tool's definition Tool name 'list_gmail_labels' and description 'List all user labels in Gmail' indicate a retrieval operation with no modification or side effects.
Risk signalsBulk/mass operation — affects multiple targets
Attacks that exploit this kind of access
List all user labels in Gmail. It is categorised as a Read tool in the Gg MCP Server, which means it retrieves data without modifying state.
Register the Gg MCP server in PolicyLayer and add a rule for list_gmail_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 Gg. Nothing to install.
list_gmail_labels 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_gmail_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.
Set action: deny in the PolicyLayer policy for list_gmail_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.
list_gmail_labels is provided by the Gg MCP server (tannht/google-cloud-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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