AI agents invoke mind_map_generate 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 executes a generation process that processes notebook sources and produces a mind map. It is not a simple read/query operation but an active execution that invokes AI generation, similar to other generative tools (audio_overview_create, flashcards_create). The output depends on source content and model processing, placing it in Execute rather than Read.
From the tool's definition 'Generate a Mind Map JSON from notebook sources' - triggers a generative operation using notebook sources
Documented attack patterns abuse exactly the kind of access mind_map_generate 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_generate:
{
"version": "1",
"default": "deny",
"tools": {
"mind_map_generate": {
"limits": [
{
"counter": "mind_map_generate_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
}mind_map_generate 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.
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Generate a Mind Map JSON from notebook sources. 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 mind_map_generate: 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_generate 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 mind_map_generate 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_generate. 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_generate 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.