AI agents use data_table_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.
The tool generates/creates a new data table artifact within a notebook. This is a Write operation as it creates new content, though it reads from existing sources to do so. It is reversible (the table can be deleted) and has no destructive, financial, or execution implications. Medium severity because it modifies notebook state but is bounded to the notebook context.
From the tool's definition 'Generate a data table from notebook sources' — creates new content (a data table) derived from existing sources
Documented attack patterns abuse exactly the kind of access data_table_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 data_table_create:
{
"version": "1",
"default": "deny",
"tools": {
"data_table_create": {
"limits": [
{
"counter": "data_table_create_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
}data_table_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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Generate a data table from notebook sources. 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 data_table_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.
data_table_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 data_table_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 data_table_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.
data_table_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.