browser_evaluate | PolicyLayer

WHAT IT DOES

What browser_evaluate does on CloudWatch Application Signals MCP Server

AI agents invoke browser_evaluate to trigger actions in CloudWatch Application Signals 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.

THE RISK

High Risk

Why browser_evaluate needs a policy

'browser_evaluate' is a common naming pattern for tools that execute arbitrary JavaScript in a browser context (e.g., Playwright's page.evaluate(), Puppeteer's page.evaluate()). This would constitute arbitrary code execution in a browser environment, making it high-risk. The description is empty, which lowers confidence, but the name is a strong signal.

From the tool's definition Tool name 'browser_evaluate' strongly suggests executing JavaScript or code in a browser context, similar to browser automation evaluate functions (e.g., Playwright/Puppeteer page.evaluate).

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

POLICY

How to control browser_evaluate

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

policy.json

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

browser_evaluate 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 CloudWatch Application Signals 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 →

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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 CloudWatch Application Signals 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_evaluate

What does the browser_evaluate tool do? +

browser_evaluate. It is categorised as a Execute tool in the CloudWatch Application Signals 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_evaluate? +

Register the CloudWatch Application Signals MCP Server MCP server in PolicyLayer and add a rule for browser_evaluate: 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 CloudWatch Application Signals MCP Server. Nothing to install.

What risk level is browser_evaluate? +

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

Can I rate-limit browser_evaluate? +

Yes. Add a rate_limit block to the browser_evaluate 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_evaluate completely? +

Set action: deny in the PolicyLayer policy for browser_evaluate. 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_evaluate? +

browser_evaluate is provided by the CloudWatch Application Signals MCP Server MCP server (awslabs.cloudwatch-applicationsignals-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 CloudWatch Application Signals MCP Server tool call.

Start from CloudWatch Application Signals MCP Server, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.

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805 CloudWatch Application Signals MCP Server tools catalogued and risk-classified — across an index of 43,000+ MCP servers.