AI agents invoke video_overview_create to trigger actions in Notebooklm. 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 initiates a generation process (video creation) in an external service. It is not a simple read or write of existing data; it executes a potentially resource-intensive AI generation task. The blast radius is medium since misuse could generate unwanted content or consume service quotas, but it does not delete data or move money.
From the tool's definition "Generate a Video Overview" — triggers an external content generation operation in Google NotebookLM
Documented attack patterns abuse exactly the kind of access video_overview_create 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 video_overview_create:
{
"version": "1",
"default": "deny",
"tools": {
"video_overview_create": {
"limits": [
{
"counter": "video_overview_create_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
}video_overview_create 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.
Generate a Video Overview for the notebook. It is categorised as a Execute tool in the Notebooklm MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Notebooklm MCP server in PolicyLayer and add a rule for video_overview_create: 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.
video_overview_create 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 video_overview_create 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 video_overview_create. 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.
video_overview_create 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.
Free to start. No card required.
29 Notebooklm tools catalogued and risk-classified — across an index of 43,000+ MCP servers.