AI agents invoke drag_rel 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 (GUI automation) and sibling tools (drag_to, click, etc.), 'drag_rel' likely performs a relative mouse drag operation. This is an Execute-category action as it triggers external GUI operations whose effects depend on arguments. Severity is high because drag operations on a desktop can interact with any application, move/drop files, or manipulate UI elements in unpredictable ways.
From the tool's definition Tool name 'drag_rel' on a GUI automation server that controls mouse, keyboard, windows, and desktop applications. No description provided.
Documented attack patterns abuse exactly the kind of access drag_rel 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 drag_rel:
{
"version": "1",
"default": "deny",
"tools": {
"drag_rel": {
"limits": [
{
"counter": "drag_rel_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
}drag_rel 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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drag_rel. 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 drag_rel: 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.
drag_rel 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 drag_rel 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 drag_rel. 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.
drag_rel 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.