browser_evaluate
Evaluate JavaScript in the page context (risk 4).
This record as markdown: /tools/yuga-hashimoto-localant/browser-evaluate.md
What browser_evaluate does on LocalAnt
AI agents invoke browser_evaluate to trigger actions in LocalAnt. 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_evaluate is rated High
Executing arbitrary JavaScript in a browser page can read/exfiltrate data, modify the DOM, make network requests, steal cookies/credentials, and interact with any web application the browser is authenticated to. The '(risk 4)' annotation from the server itself also signals maximum risk. This is a powerful code execution primitive with a very large blast radius.
From the tool's definition "Evaluate JavaScript in the page context" — arbitrary JS execution in a live browser context
Attacks that exploit this kind of access
The rule that runs browser_evaluate safely
PolicyLayer is an MCP gateway: it sits between your AI agents and LocalAnt, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For browser_evaluate, this is the rule to start with:
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.
The button opens the PolicyLayer dashboard: create your workspace, connect LocalAnt, apply this rule, and every browser_evaluate call is checked against it from then on.
Questions about browser_evaluate
Evaluate JavaScript in the page context (risk 4). It is categorised as a Execute tool in the LocalAnt MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the LocalAnt 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 LocalAnt. Nothing to install.
browser_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 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.
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.
browser_evaluate is provided by the LocalAnt MCP server (yuga-hashimoto/localant). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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