Get Lighthouse score and reports for accessibility, SEO and best practices. This excludes performance. For performance audits, run ${startTrace.name}
AI agents invoke lighthouse_audit to trigger actions in Chrome Devtools. What it does depends on the arguments the agent supplies, and its effects often reach beyond the immediate call — builds kicked off, notifications sent, workflows started.
Lighthouse audits execute code within the browser context to analyze accessibility, SEO, and best practices. While the operation itself is non-destructive and read-focused in intent, it performs active browser inspection and analysis that qualifies as Execute rather than Read because: (1) it runs a complex external tool (Lighthouse) with side effects like resource consumption and timing impacts, (2) the results…
From the tool's definition Tool runs Lighthouse audits which trigger analysis operations on a live Chrome browser. The description states it 'Get[s] Lighthouse score and reports' and references performance tracing (${startTrace.name}), indicating it executes external browser operations…
Attacks that exploit this kind of access
Get Lighthouse score and reports for accessibility, SEO and best practices. This excludes performance. For performance audits, run ${startTrace.name}. It is categorised as a Execute tool in the Chrome Devtools MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Chrome Devtools MCP server in PolicyLayer and add a rule for lighthouse_audit: 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 Devtools. Nothing to install.
lighthouse_audit 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 lighthouse_audit 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 lighthouse_audit. 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.
lighthouse_audit is provided by the Chrome Devtools MCP server (shivamprasad99/chrome-devtools-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
lighthouse_audit is one line of Chrome Devtools's registry record.
The record carries the whole server: verified identity, auth posture, risk grade, every tool classified, recommended policy — re-checked continuously.
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