AI agents invoke menu_click to trigger actions in ScreenHand. 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.
Clicking menu items triggers application actions which can have wide-ranging side effects depending on the menu item selected (e.g., closing files, opening dialogs, executing commands, deleting data). The effect is determined by runtime arguments, making this Execute. Severity is high because an AI agent could trigger destructive or sensitive application commands through menu interactions.
From the tool's definition Click a menu item in an app
Documented attack patterns abuse exactly the kind of access menu_click gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and ScreenHand, and nothing reaches the server without passing your rules. This is the rule we recommend for menu_click:
{
"version": "1",
"default": "deny",
"tools": {
"menu_click": {
"limits": [
{
"counter": "menu_click_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
} menu_click 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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Click a menu item in an app. It is categorised as a Execute tool in the ScreenHand MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the ScreenHand MCP server in PolicyLayer and add a rule for menu_click: 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 ScreenHand. Nothing to install.
menu_click 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 menu_click 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 menu_click. 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.
menu_click is provided by the ScreenHand MCP server (manushi4/screenhand). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from ScreenHand, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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