Add text to the end of a Google Document
AI agents use append_text to create or update resources in LLM2Docs (Unofficial) — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your LLM2Docs (Unofficial) environment.
This tool creates or modifies data in a reversible manner (text can be edited or deleted afterward). It is not destructive since appended text can be undone. It does not execute arbitrary code, delete data irreversibly, or involve financial operations.
From the tool's definition Tool name 'append_text' and description 'Add text to the end of a Google Document' clearly indicate modification of document content.
Attacks that exploit this kind of access
Add text to the end of a Google Document. It is categorised as a Write tool in the LLM2Docs (Unofficial) MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the LLM2Docs (Unofficial) MCP server in PolicyLayer and add a rule for append_text: 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 LLM2Docs (Unofficial). Nothing to install.
append_text 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_text 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_text. 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_text is provided by the LLM2Docs (Unofficial) MCP server (nomannayeem/google-docs-mcp-server). 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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