browser_tabs

THE RISK

Low Risk

Why browser_tabs needs a policy

With no description available, it is impossible to determine what this tool does. The name 'browser_tabs' seems out of place for an AWS SageMaker MCP server, suggesting it may be a UI utility or misattributed tool. Confidence is very low; defaulting to Other with low severity.

From the tool's definition Tool description is empty and uninformative; the name 'browser_tabs' does not clearly map to any SageMaker AI operation.

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

POLICY

How to control browser_tabs

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_tabs:

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "browser_tabs": {
      "limits": [
        {
          "counter": "browser_tabs_rate",
          "window": "minute",
          "max": 60,
          "scope": "grant"
        }
      ]
    }
  }
}

browser_tabs gets a rate cap, and everything else on the server is denied unless you say otherwise.

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

SET A RULE FOR THIS TOOL →

Free to start. No card required.

EXPLORE

Related tools and policies

More Amazon SageMaker AI MCP Server tools

Destructive bulk_delete_by_criteria bulk_delete_by_criteria Destructive cache_delete Delete a value from the cache. Destructive cache_delete_many Delete multiple values from the cache. Destructive cache_delete_multi Delete multiple values from the cache (alias for delete_many). Destructive cancel_logs_insight_query cancel_logs_insight_query Destructive CancelAHORunBatch CancelAHORunBatch Destructive delete delete Destructive delete_access_key delete_access_key

All 805 Amazon SageMaker AI MCP Server tools →

Other tools on other servers

Android Forensics ADB MCP Server generate_app_analysis_report Ethereum Tools add Math MCP Server complex_analysis_suite Crypto_MCP aes_encrypt

Go deeper

The MCP Attack Database → Documented attack patterns against MCP deployments — and the policies that stop them.
Tool risk categories → How PolicyLayer classifies MCP tools by what they can do.
MCP tool → What an MCP tool is and how clients discover and call it.
Rate Limiting MCP Tool Calls: A Practical Guide →
MCP Security: Why Prompt Guardrails Aren't Enough →

FAQ

Questions about browser_tabs

What does the browser_tabs tool do? +

browser_tabs. It is categorised as a Other tool in the Amazon SageMaker AI MCP Server MCP Server, which means it performs auxiliary operations.

How do I enforce a policy on browser_tabs? +

Register the Amazon SageMaker AI MCP Server MCP server in PolicyLayer and add a rule for browser_tabs: 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_tabs? +

browser_tabs is a Other tool with low risk. Read-only tools are generally safe to allow by default.

Can I rate-limit browser_tabs? +

Yes. Add a rate_limit block to the browser_tabs 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_tabs completely? +

Set action: deny in the PolicyLayer policy for browser_tabs. 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_tabs? +

browser_tabs 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.

CHECK YOUR STACK →