Run a JavaScript expression in the page context and return the result.
AI agents invoke browser_eval to trigger actions in Taw Computer. 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 tool executes JavaScript expressions with results that depend on the provided code argument. This qualifies as Execute rather than Read because it can trigger side effects beyond data retrieval—JavaScript can modify DOM, trigger network requests, interact with APIs, or execute any browser-accessible operation.
From the tool's definition Tool description states: 'Run a JavaScript expression in the page context and return the result.' This directly executes arbitrary code (JavaScript) in the browser environment.
Documented attack patterns abuse exactly the kind of access browser_eval gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Taw Computer, and nothing reaches the server without passing your rules. This is the rule we recommend for browser_eval:
{
"version": "1",
"default": "deny",
"tools": {
"browser_eval": {
"limits": [
{
"counter": "browser_eval_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
}browser_eval 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.
Free to start. No card required.
Run a JavaScript expression in the page context and return the result. It is categorised as a Execute tool in the Taw Computer MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Taw Computer MCP server in PolicyLayer and add a rule for browser_eval: 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 Taw Computer. Nothing to install.
browser_eval 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_eval 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_eval. 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_eval is provided by the Taw Computer MCP server (tawgroup/taw-computer). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Taw Computer, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
Free to start. No card required.
36 Taw Computer tools catalogued and risk-classified — across an index of 43,000+ MCP servers.