AI agents invoke resize_window to trigger actions in PyMCPAutoGUI. 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.
Based on the server context and sibling tools (activate_window, close_window, drag_to, etc.), this tool almost certainly resizes a desktop window — a GUI automation action that triggers an external operation. Empty description lowers confidence. Resizing is reversible and low blast-radius but still an Execute-category action as it manipulates the desktop environment.
From the tool's definition Tool name 'resize_window' on a GUI automation server that 'control[s] mouse, keyboard, windows'. Description is empty and uninformative.
Documented attack patterns abuse exactly the kind of access resize_window gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and PyMCPAutoGUI, and nothing reaches the server without passing your rules. This is the rule we recommend for resize_window:
{
"version": "1",
"default": "deny",
"tools": {
"resize_window": {
"limits": [
{
"counter": "resize_window_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
}resize_window 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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resize_window. It is categorised as a Execute tool in the PyMCPAutoGUI MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the PyMCPAutoGUI MCP server in PolicyLayer and add a rule for resize_window: 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 PyMCPAutoGUI. Nothing to install.
resize_window 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 resize_window 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 resize_window. 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.
resize_window is provided by the PyMCPAutoGUI MCP server (kitfactory/pymcpautogui). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from PyMCPAutoGUI, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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34 PyMCPAutoGUI tools catalogued and risk-classified — across an index of 43,000+ MCP servers.