AI agents invoke browser_wait 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.
While waiting itself is passive, browser_wait is explicitly designed to support automated browser control and triggers dependent actions. It functions as a control-flow tool enabling Execute-category operations. The server's accessibility API integration and native UI automation context elevates this from passive monitoring to part of an active execution framework.
From the tool's definition Tool enables waiting for conditions on Chrome/Electron pages, which is a prerequisite for triggering subsequent automated actions.
Documented attack patterns abuse exactly the kind of access browser_wait 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 browser_wait:
{
"version": "1",
"default": "deny",
"tools": {
"browser_wait": {
"limits": [
{
"counter": "browser_wait_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
}browser_wait 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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Wait for a condition on a Chrome/Electron page. 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 browser_wait: 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.
browser_wait 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 browser_wait 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 browser_wait. 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.
browser_wait 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.
Free to start. No card required.
89 ScreenHand tools catalogued and risk-classified — across an index of 43,000+ MCP servers.