Select an element on the page with Select tag
AI agents invoke puppeteer_select to trigger actions in Puppeteer MCP Server. 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 action (selecting a dropdown/select element on a web page), which constitutes executing an external operation whose effects depend on the arguments provided. While selecting a value in a form element is relatively benign on its own, it can trigger JavaScript events, form submissions, or page state changes, placing it in the Execute category.
From the tool's definition 'Select an element on the page with Select tag' — triggers a browser interaction (selecting a form element) via Puppeteer automation
Documented attack patterns abuse exactly the kind of access puppeteer_select gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Puppeteer MCP Server, and nothing reaches the server without passing your rules. This is the rule we recommend for puppeteer_select:
{
"version": "1",
"default": "deny",
"tools": {
"puppeteer_select": {
"limits": [
{
"counter": "puppeteer_select_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
}puppeteer_select 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 element on the page with Select tag. It is categorised as a Execute tool in the Puppeteer MCP Server MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Puppeteer MCP Server MCP server in PolicyLayer and add a rule for puppeteer_select: 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 Puppeteer MCP Server. Nothing to install.
puppeteer_select 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 puppeteer_select 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 puppeteer_select. 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.
puppeteer_select is provided by the Puppeteer MCP Server MCP server (merajmehrabi/puppeteer-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Puppeteer MCP Server, 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.
8 Puppeteer MCP Server tools catalogued and risk-classified — across an index of 43,000+ MCP servers.