AI agents invoke browser_select_option to trigger actions in YetiBrowser MCP. 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 performs a browser automation action (selecting a dropdown option) in a live browser session. It executes an interaction that can trigger form changes, navigation, or other side effects depending on the page context. It goes beyond reading data and constitutes an active browser operation, placing it in the Execute category.
From the tool's definition Select an option in a dropdown — triggers browser interaction/automation in an active Chrome tab
Documented attack patterns abuse exactly the kind of access browser_select_option gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and YetiBrowser MCP, and nothing reaches the server without passing your rules. This is the rule we recommend for browser_select_option:
{
"version": "1",
"default": "deny",
"tools": {
"browser_select_option": {
"limits": [
{
"counter": "browser_select_option_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
} browser_select_option 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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Select an option in a dropdown. It is categorised as a Execute tool in the YetiBrowser MCP MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the YetiBrowser MCP server in PolicyLayer and add a rule for browser_select_option: 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 YetiBrowser MCP. Nothing to install.
browser_select_option 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_select_option 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_select_option. 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_select_option is provided by the YetiBrowser MCP server (yetidevworks/yetibrowser-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from YetiBrowser MCP, 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.
17 YetiBrowser MCP tools catalogued and risk-classified — across an index of 43,000+ MCP servers.