AI agents use mind_map_save 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 or modifies notebook content by saving a mind map. While reversible (the save could be undone via other operations), it materially changes the state of a notebook. It does not execute arbitrary code, delete data irreversibly, or move money. It fits the Write category as a data creation/modification action with side effects that depend on which notebook and mind map content is provided.
From the tool's definition Tool name 'mind_map_save' and description 'Save a generated Mind Map to a notebook' indicate data creation/modification. The action persists a mind map artifact to a notebook, which is a reversible write operation.
Documented attack patterns abuse exactly the kind of access mind_map_save 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 mind_map_save:
{
"version": "1",
"default": "deny",
"tools": {
"mind_map_save": {
"limits": [
{
"counter": "mind_map_save_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
}mind_map_save 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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Save a generated Mind Map to a 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 mind_map_save: 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.
mind_map_save 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 mind_map_save 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 mind_map_save. 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.
mind_map_save 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.