AI agents use append_to_document to create or update resources in Gg — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Gg environment.
The tool modifies existing document data by appending text, which is a Write operation. It does not delete or irreversibly destroy data (not Destructive), does not execute arbitrary code (not Execute), and does not involve financial transactions (not Financial).
From the tool's definition Tool name 'append_to_document' and description 'Append text to the end of a Google Docs document' indicate creation/modification of document content in a reversible manner.
Attacks that exploit this kind of access
Append text to the end of a Google Docs document. It is categorised as a Write tool in the Gg MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Gg MCP server in PolicyLayer and add a rule for append_to_document: 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.
append_to_document 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 append_to_document 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 append_to_document. 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.
append_to_document 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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