update_message_feedback · CustomGPT MCP Server MCP

WHAT IT DOES

What update_message_feedback does on CustomGPT MCP Server

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

WHY IT NEEDS A POLICY

Why update_message_feedback needs a policy

The tool modifies existing feedback data (thumbs up/down reactions) rather than creating new content from scratch (Write rather than Execute). The change is reversible and non-destructive. Severity is low because feedback reactions are low-impact metadata with minimal blast radius—misuse would only affect user-facing feedback signals, not core application functionality or sensitive data.

From the tool's definition Tool name 'update_message_feedback' and description 'Update feedback reaction for a specific message (thumbs up/down)' indicate modification of feedback metadata associated with messages.

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

update_message_feedback Rate-limited

update_message_feedback 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": {
    "update_message_feedback": {
      "limits": [
        {
          "counter": "update_message_feedback_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 CustomGPT MCP Server, so you can run agents against it safely.

FAQ

Questions about update_message_feedback

What does the update_message_feedback tool do? +

Update feedback reaction for a specific message (thumbs up/down). It is categorised as a Write tool in the CustomGPT 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 update_message_feedback? +

Register the CustomGPT MCP Server MCP server in PolicyLayer and add a rule for update_message_feedback: 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 CustomGPT MCP Server. Nothing to install.

What risk level is update_message_feedback? +

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

Can I rate-limit update_message_feedback? +

Yes. Add a rate_limit block to the update_message_feedback 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 update_message_feedback completely? +

Set action: deny in the PolicyLayer policy for update_message_feedback. 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 update_message_feedback? +

update_message_feedback is provided by the CustomGPT MCP Server MCP server (poll-the-people/customgpt-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.