High Risk →

browser_click

browser_click

How to control browser_click ↓

What browser_click does on Amazon SageMaker AI MCP Server

AI agents invoke browser_click to trigger actions in Amazon SageMaker AI MCP Server. 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.

High Risk

Why browser_click needs a policy

The name 'browser_click' strongly suggests this tool performs browser automation by clicking elements, which is an Execute-category action. Browser clicks can trigger external operations, form submissions, navigation, or other side effects depending on what is clicked. The description is empty, which reduces confidence, but the name is highly indicative.

From the tool's definition Tool name: 'browser_click' — implies triggering a browser UI action

Documented attack patterns abuse exactly the kind of access browser_click gives an agent:

How to control browser_click

PolicyLayer is an MCP gateway — it sits between your AI agents and Amazon SageMaker AI MCP Server, and nothing reaches the server without passing your rules. This is the rule we recommend for browser_click:

policy.json
{
  "version": "1",
  "default": "deny",
  "tools": {
    "browser_click": {
      "limits": [
        {
          "counter": "browser_click_rate",
          "window": "minute",
          "max": 10,
          "scope": "grant"
        }
      ]
    }
  }
}

browser_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.

  1. Create a free account and register Amazon SageMaker AI MCP Server — nothing to install.
  2. Add this policy — paste it, or build it visually.
  3. Point your MCP client (Claude, Cursor, anything) at your gateway URL.
RATE-LIMIT THIS TOOL →

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Related tools and policies

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Questions about browser_click

What does the browser_click tool do? +

browser_click. It is categorised as a Execute tool in the Amazon SageMaker AI MCP Server MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.

How do I enforce a policy on browser_click? +

Register the Amazon SageMaker AI MCP Server MCP server in PolicyLayer and add a rule for browser_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 Amazon SageMaker AI MCP Server. Nothing to install.

What risk level is browser_click? +

browser_click is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.

Can I rate-limit browser_click? +

Yes. Add a rate_limit block to the browser_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.

How do I block browser_click completely? +

Set action: deny in the PolicyLayer policy for browser_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.

What MCP server provides browser_click? +

browser_click is provided by the Amazon SageMaker AI MCP Server MCP server (awslabs.sagemaker-ai-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every Amazon SageMaker AI MCP Server tool call.

Start from Amazon SageMaker AI MCP Server, 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.

805 Amazon SageMaker AI MCP Server tools catalogued and risk-classified — across an index of 43,000+ MCP servers.

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