record_agent_execution_feedback · MCP SAPUI5 Server MCP

WHAT IT DOES

What record_agent_execution_feedback does on MCP SAPUI5 Server

AI agents use record_agent_execution_feedback to create or update resources in MCP SAPUI5 Server — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your MCP SAPUI5 Server environment.

WHY IT NEEDS A POLICY

Why record_agent_execution_feedback needs a policy

The tool writes data to local JSONL logs and updates aggregate metrics. This is a reversible data modification (Write category) with no destructive capability, no external financial impact, and no code execution. The scope is limited to feedback logging and metric updates.

From the tool's definition Tool name and description indicate it 'Record agent execution feedback in local JSONL log and update aggregate pack metrics'—this involves creating/modifying log entries and metrics data in files.

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

record_agent_execution_feedback Rate-limited

record_agent_execution_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": {
    "record_agent_execution_feedback": {
      "limits": [
        {
          "counter": "record_agent_execution_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 MCP SAPUI5 Server, so you can run agents against it safely.

FAQ

Questions about record_agent_execution_feedback

What does the record_agent_execution_feedback tool do? +

Record agent execution feedback in local JSONL log and update aggregate pack metrics for future ranking and promotion. It is categorised as a Write tool in the MCP SAPUI5 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 record_agent_execution_feedback? +

Register the MCP SAPUI5 Server MCP server in PolicyLayer and add a rule for record_agent_execution_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 MCP SAPUI5 Server. Nothing to install.

What risk level is record_agent_execution_feedback? +

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

Can I rate-limit record_agent_execution_feedback? +

Yes. Add a rate_limit block to the record_agent_execution_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 record_agent_execution_feedback completely? +

Set action: deny in the PolicyLayer policy for record_agent_execution_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 record_agent_execution_feedback? +

record_agent_execution_feedback is provided by the MCP SAPUI5 Server MCP server (santiagosanmartinn/mcpui5server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.