AI agents invoke evaluate to trigger actions in Chrome Debug 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.
This tool executes JavaScript code in the browser, which can perform any action the browser can perform: access DOM, make network requests, steal data, manipulate pages, trigger user actions, or exploit browser vulnerabilities. The impact depends entirely on what code the AI agent injects, making this a high-severity Execute action.
From the tool's definition Tool name 'evaluate' with description 'Evaluate JavaScript in Chrome' indicates execution of arbitrary code within the browser context. The server description also mentions 'page automation' and 'userscript injection', confirming code execution capabilities.
Documented attack patterns abuse exactly the kind of access evaluate gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Chrome Debug MCP Server, and nothing reaches the server without passing your rules. This is the rule we recommend for evaluate:
{
"version": "1",
"default": "deny",
"tools": {
"evaluate": {
"limits": [
{
"counter": "evaluate_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
}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.
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Evaluate JavaScript in Chrome. It is categorised as a Execute tool in the Chrome Debug MCP Server MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Chrome Debug MCP Server MCP server in PolicyLayer and add a rule for 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 Chrome Debug MCP Server. Nothing to install.
evaluate 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 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.
Set action: deny in the PolicyLayer policy for 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.
evaluate is provided by the Chrome Debug MCP Server MCP server (robertheadley/chrome-debug-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 3 Chrome Debug MCP Server tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
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3 Chrome Debug MCP Server tools catalogued and risk-classified — across an index of 42,500+ MCP servers.