Stop the automated daily ML model retraining scheduler
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.
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.
Documented attack patterns abuse exactly the kind of access stop_auto_retraining gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Mcp Windows, and nothing reaches the server without passing your rules. This is the rule we recommend for stop_auto_retraining:
{
"version": "1",
"default": "deny",
"tools": {
"stop_auto_retraining": {
"limits": [
{
"counter": "stop_auto_retraining_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
}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.
Free to start. No card required.
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.
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.
stop_auto_retraining is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.
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.
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.
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.
Deterministic rules across all 441 Mcp Windows tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
Free to start. No card required.
441 Mcp Windows tools catalogued and risk-classified — across an index of 42,500+ MCP servers.