Manually trigger ML model retraining (bypasses schedule)
AI agents invoke trigger_manual_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.
This tool executes a computational process (ML model retraining) that can consume significant system resources, modify model files, and potentially impact dependent systems relying on the model. While not immediately destructive or creating new data in a user-facing sense, it actively triggers and controls a system operation with side effects.
From the tool's definition Tool description states 'Manually trigger ML model retraining (bypasses schedule)' - this action runs/triggers an external operation (model retraining) whose effects depend on system state and training configuration.
Documented attack patterns abuse exactly the kind of access trigger_manual_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 trigger_manual_retraining:
{
"version": "1",
"default": "deny",
"tools": {
"trigger_manual_retraining": {
"limits": [
{
"counter": "trigger_manual_retraining_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
}trigger_manual_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.
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Manually trigger ML model retraining (bypasses schedule). 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 trigger_manual_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.
trigger_manual_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 trigger_manual_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 trigger_manual_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.
trigger_manual_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.