browser_resize

THE RISK

High Risk

Why browser_resize needs a policy

The name 'browser_resize' implies a browser interaction/action, which falls under the Execute category as it triggers an external operation (browser window manipulation). However, the empty description severely limits confidence. Given the AWS MCP server context, this could be part of browser automation used for AWS Console interactions.

From the tool's definition Tool name 'browser_resize' suggests a browser action (resizing a browser window), but the description is empty and uninformative.

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

POLICY

How to control browser_resize

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

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "browser_resize": {
      "limits": [
        {
          "counter": "browser_resize_rate",
          "window": "minute",
          "max": 10,
          "scope": "grant"
        }
      ]
    }
  }
}

browser_resize 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.

Create a free account and register AWS API 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.

RATE-LIMIT THIS TOOL →

Free to start. No card required.

EXPLORE

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Go deeper

Govern code and CI agents → Branch allowlists, approval on merges, and rate caps on the build and pipeline tools agents trigger.
High-risk tools in AWS API MCP Server → Every high-risk tool this server exposes, in one view.
All high-risk MCP tools → Every high-risk tool across the catalogue, and the policy pattern that contains them.
The MCP Attack Database → Documented attack patterns against MCP deployments — and the policies that stop them.
Agent sandbox → Bounding what an agent can execute and where the boundary should sit.
Least privilege for MCP → Granting agents the minimum tool surface the task needs.
Rate Limiting MCP Tool Calls: A Practical Guide →
MCP Security: Why Prompt Guardrails Aren't Enough →
PolicyLayer vs alternatives → How deterministic, per-call MCP policy compares with gateways, identity layers, and authorisation platforms.

FAQ

Questions about browser_resize

What does the browser_resize tool do? +

browser_resize. It is categorised as a Execute tool in the AWS API 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_resize? +

Register the AWS API MCP Server MCP server in PolicyLayer and add a rule for browser_resize: 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 AWS API MCP Server. Nothing to install.

What risk level is browser_resize? +

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

Can I rate-limit browser_resize? +

Yes. Add a rate_limit block to the browser_resize 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_resize completely? +

Set action: deny in the PolicyLayer policy for browser_resize. 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_resize? +

browser_resize is provided by the AWS API MCP Server MCP server (awslabs.aws-api-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 AWS API MCP Server tool call.

Start from AWS API 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 →