browser_performance_observer
Atomic primitive: subscribe to PerformanceObserver entry types in the active page and return both buffered and live entries observed during a collection window. Entry types are passed through to PerformanceObserver.observe({ type }) verbatim (e.g. largest-contentful-paint, layout-shift, longtask,...
This record as markdown: /tools/io-github-vmoranv-jshookmcp/browser-performance-observer.md
What browser_performance_observer does on Jshookmcp
AI agents invoke browser_performance_observer to trigger actions in Jshookmcp. 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.
Why browser_performance_observer is rated High
Executes browser-side JavaScript observer in active page, triggering external browser operations.
From the tool's definition subscribe to PerformanceObserver entry types in the active page
Attacks that exploit this kind of access
The rule that runs browser_performance_observer safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Jshookmcp, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For browser_performance_observer, this is the rule to start with:
browser_performance_observer 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.
The button opens the PolicyLayer dashboard: create your workspace, connect Jshookmcp, apply this rule, and every browser_performance_observer call is checked against it from then on.
Questions about browser_performance_observer
Atomic primitive: subscribe to PerformanceObserver entry types in the active page and return both buffered and live entries observed during a collection window. Entry types are passed through to PerformanceObserver.observe({ type }) verbatim (e.g. largest-contentful-paint, layout-shift, longtask, event, long-animation-frame); unsupported entry types are skipped silently. One observer per type — the API does not accept multiple types in a single observe() call. It is categorised as a Execute tool in the Jshookmcp MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Jshook MCP server in PolicyLayer and add a rule for browser_performance_observer: 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 Jshookmcp. Nothing to install.
browser_performance_observer 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 browser_performance_observer 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 browser_performance_observer. 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.
browser_performance_observer is provided by the Jshook MCP server (@jshookmcp/jshook). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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