Select an element on the page with Select tag
AI agents invoke puppeteer_select to trigger actions in MCP-Brave-Search. 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 an element on a web page), which constitutes an Execute-category operation as it triggers external browser interactions whose effects depend on the arguments provided. While it's a UI interaction rather than code execution, it can manipulate web page state and potentially trigger downstream actions.
From the tool's definition Select an element on the page with Select tag
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 MCP-Brave-Search, 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 MCP-Brave-Search MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the MCP-Brave-Search 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 MCP-Brave-Search. 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 MCP-Brave-Search MCP server (modelcontextprotocol/servers-archived). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from MCP-Brave-Search, 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.
59 MCP-Brave-Search tools catalogued and risk-classified — across an index of 43,000+ MCP servers.