AI agents use notebook_create to create or update resources in Notebooklm — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Notebooklm environment.
This tool creates a new notebook, which is a reversible Write operation. It modifies the user's NotebookLM workspace by adding a new notebook but does not permanently destroy data or execute arbitrary code. The severity is medium because misuse could lead to creation of numerous notebooks consuming resources or polluting the user's workspace, but the action is recoverable by deletion.
From the tool's definition Tool name 'notebook_create' and description 'Create a new notebook' indicate creation of new data structure within Google NotebookLM.
Documented attack patterns abuse exactly the kind of access notebook_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 notebook_create:
{
"version": "1",
"default": "deny",
"tools": {
"notebook_create": {
"limits": [
{
"counter": "notebook_create_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
}notebook_create stays usable, but capped — an agent stuck in a loop can't make hundreds of changes a minute. Everything else on the server is denied unless you say otherwise.
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Create a new notebook. It is categorised as a Write tool in the Notebooklm MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Notebooklm MCP server in PolicyLayer and add a rule for notebook_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.
notebook_create is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.
Yes. Add a rate_limit block to the notebook_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 notebook_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.
notebook_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.
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29 Notebooklm tools catalogued and risk-classified — across an index of 43,000+ MCP servers.