Alias for browser_click — both use realistic mouseMoved → mousePressed → mouseReleased events. Prefer browser_click directly.
AI agents invoke browser_human_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.
This tool triggers real browser mouse events (move, press, release) which constitutes executing UI actions in the browser. It can interact with any clickable element including forms, buttons, and links, making it an Execute-category tool.
From the tool's definition Alias for browser_click — both use realistic mouseMoved → mousePressed → mouseReleased events
Documented attack patterns abuse exactly the kind of access browser_human_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 browser_human_click:
{
"version": "1",
"default": "deny",
"tools": {
"browser_human_click": {
"limits": [
{
"counter": "browser_human_click_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
}browser_human_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.
Free to start. No card required.
Alias for browser_click — both use realistic mouseMoved → mousePressed → mouseReleased events. Prefer browser_click directly. 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_human_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.
browser_human_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 browser_human_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 browser_human_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.
browser_human_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.
Free to start. No card required.
89 ScreenHand tools catalogued and risk-classified — across an index of 43,000+ MCP servers.