stop_auto_retraining

Stop the automated daily ML model retraining scheduler

SERVERMcp Windows SOURCEmukul975/mcp-windows-automation

High RISK CLASS

Category Execute

Parameters 00 required

Recommended Rate-limitedsee the rule below

Registry record Grade F, identity unverified Pull the record →

This record as markdown: /tools/mukul975-mcp-windows-automation/stop-auto-retraining.md

WHAT IT DOES

What stop_auto_retraining does on Mcp Windows

AI agents invoke stop_auto_retraining to trigger actions in Mcp Windows. What it does depends on the arguments the agent supplies, and its effects often reach beyond the immediate call: builds kicked off, notifications sent, workflows started.

RISK

Why stop_auto_retraining is rated High

The tool executes a command to halt a scheduled process (ML model retraining). While not destructive (the retraining can be resumed) and not immediately data-damaging, it is an Execute-class action because it manipulates system operations and external service behavior.

From the tool's definition Tool stops an automated scheduler process ('Stop the automated daily ML model retraining scheduler'). This is an Execute action that triggers/halts an external operation whose effects depend on system state.

Attacks that exploit this kind of access

RECOMMENDED RULE

The rule that runs stop_auto_retraining safely

PolicyLayer is an MCP gateway: it sits between your AI agents and Mcp Windows, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For stop_auto_retraining, this is the rule to start with:

stop_auto_retraining Rate-limited

stop_auto_retraining stays usable, but rate-capped: a runaway agent can't fire it dozens of times a minute. Everything else on the server is denied unless you say otherwise.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "stop_auto_retraining": {
      "limits": [
        {
          "counter": "stop_auto_retraining_rate",
          "window": "minute",
          "max": 10,
          "scope": "grant"
        }
      ]
    }
  }
}

RATE-LIMIT THIS TOOL → Instant setup, no code required.

The button opens the PolicyLayer dashboard: create your workspace, connect Mcp Windows, apply this rule, and every stop_auto_retraining call is checked against it from then on.

FAQ

Questions about stop_auto_retraining

What does the stop_auto_retraining tool do? +

Stop the automated daily ML model retraining scheduler. It is categorised as a Execute tool in the Mcp Windows MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.

How do I enforce a policy on stop_auto_retraining? +

Register the Mcp Windows MCP server in PolicyLayer and add a rule for stop_auto_retraining: 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 Windows. Nothing to install.

What risk level is stop_auto_retraining? +

stop_auto_retraining is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.

Can I rate-limit stop_auto_retraining? +

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

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

stop_auto_retraining is provided by the Mcp Windows MCP server (mukul975/mcp-windows-automation). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

KEEP EXPLORING

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