add_preference · Google Workspace MCP Server MCP

WHAT IT DOES

What add_preference does on Google Workspace MCP Server

AI agents use add_preference to create or update resources in Google Workspace MCP Server — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Google Workspace MCP Server environment.

WHY IT NEEDS A POLICY

Why add_preference needs a policy

This tool creates or modifies user preference records in local storage. It has no destructive capability (preferences can be updated/overwritten reversibly), does not execute code or shell commands, and does not move money. It is a straightforward Write operation with low blast radius—misuse would only affect stored preference data, not system integrity or financial resources.

From the tool's definition Tool name 'add_preference' and description 'Store user preferences' indicate creation/modification of preference data in a personal memory system. The verb 'add' and 'Store' confirm data writing without deletion or execution of external operations.

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

add_preference Rate-limited

add_preference stays usable, but capped — an agent stuck in a loop can't make hundreds of changes a minute. Everything else on the server is denied unless you say otherwise.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "add_preference": {
      "limits": [
        {
          "counter": "add_preference_rate",
          "window": "minute",
          "max": 30,
          "scope": "grant"
        }
      ]
    }
  }
}

LIMIT THIS TOOL →

Instant setup, no code required.

PolicyLayer is an MCP gateway: every tool call is checked against your rule before it reaches Google Workspace MCP Server, so you can run agents against it safely.

FAQ

Questions about add_preference

What does the add_preference tool do? +

Store user preferences - what they like/dislike, how they want things done. It is categorised as a Write tool in the Google Workspace MCP Server MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on add_preference? +

Register the Google Workspace MCP Server MCP server in PolicyLayer and add a rule for add_preference: 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 Google Workspace MCP Server. Nothing to install.

What risk level is add_preference? +

add_preference is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.

Can I rate-limit add_preference? +

Yes. Add a rate_limit block to the add_preference 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.

How do I block add_preference completely? +

Set action: deny in the PolicyLayer policy for add_preference. 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.

What MCP server provides add_preference? +

add_preference is provided by the Google Workspace MCP Server MCP server (pbulbule13/google-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.