Check status of studio artifacts (Audio, Video, Report, etc.)
AI agents call studio_poll to retrieve information from Notebooklm without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool retrieves the current state of studio artifacts (Audio, Video, Report, etc.) without creating, modifying, deleting, or executing any operations. It is a simple read/query operation to obtain status information. The action is non-destructive and has no side effects beyond retrieving data, making it a Read category risk with low severity.
From the tool's definition Tool name 'studio_poll' and description 'Check status of studio artifacts' indicate a status-checking/polling operation with no data modification or external command execution.
Documented attack patterns abuse exactly the kind of access studio_poll gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Notebooklm, and nothing reaches the server without passing your rules. This is the rule we recommend for studio_poll:
{
"version": "1",
"default": "deny",
"tools": {
"studio_poll": {}
}
}studio_poll is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
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Check status of studio artifacts (Audio, Video, Report, etc.). It is categorised as a Read tool in the Notebooklm MCP Server, which means it retrieves data without modifying state.
Register the Notebooklm MCP server in PolicyLayer and add a rule for studio_poll: 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 Notebooklm. Nothing to install.
studio_poll is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the studio_poll 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 studio_poll. 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.
studio_poll is provided by the Notebooklm MCP server (moodrobotics/notebooklm-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Notebooklm, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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29 Notebooklm tools catalogued and risk-classified — across an index of 43,000+ MCP servers.