Create multiple NotebookLM notebooks in one operation. ## What This Tool Does - Creates up to 10 notebooks in a single batch operation - Reports progress for each notebook - Optionally continues on error or stops on first failure - Auto-adds created notebooks to your library ## Example Usage ``...
High parameter count (10 properties)
Part of the Notebooklm MCP server. Enforce policies on this tool with Intercept, the open-source MCP proxy.
AI agents use batch_create_notebooks to create or modify resources in Notebooklm. Write operations carry medium risk because an autonomous agent could trigger bulk unintended modifications. Rate limits prevent a single agent session from making hundreds of changes in rapid succession. Argument validation ensures the agent passes expected values.
Without a policy, an AI agent could call batch_create_notebooks repeatedly, creating or modifying resources faster than any human could review. Intercept's rate limiting ensures write operations happen at a controlled pace, and argument validation catches malformed or unexpected inputs before they reach Notebooklm.
Write tools can modify data. A rate limit prevents runaway bulk operations from AI agents.
tools:
batch_create_notebooks:
rules:
- action: allow
rate_limit:
max: 30
window: 60See the full Notebooklm policy for all 31 tools.
Agents calling write-class tools like batch_create_notebooks have been implicated in these attack patterns. Read the full case and prevention policy for each:
Other tools in the Write risk category across the catalogue. The same policy patterns (rate-limit, validate) apply to each.
Create multiple NotebookLM notebooks in one operation. ## What This Tool Does - Creates up to 10 notebooks in a single batch operation - Reports progress for each notebook - Optionally continues on error or stops on first failure - Auto-adds created notebooks to your library ## Example Usage ```json { "notebooks": [ { "name": "React Documentation", "sources": [ { "type": "url", "value": "https://react.dev/reference" } ], "topics": ["react", "frontend"] }, { "name": "Node.js API", "sources": [ { "type": "url", "value": "https://nodejs.org/api/" } ], "topics": ["nodejs", "backend"] } ], "stop_on_error": false } ``` ## Limits - Maximum 10 notebooks per batch - Each notebook follows individual source limits (50-600 based on tier) - Delays between notebooks to avoid rate limiting ## Returns Summary with: - total: Number of notebooks attempted - succeeded: Successfully created count - failed: Failed count - results: Array of individual results. 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.
Add a rule in your Intercept YAML policy under the tools section for batch_create_notebooks. You can allow, deny, rate-limit, or validate arguments. Then run Intercept as a proxy in front of the Notebooklm MCP server.
batch_create_notebooks 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 batch_create_notebooks rule in your Intercept 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 Intercept policy for batch_create_notebooks. 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.
batch_create_notebooks is provided by the Notebooklm MCP server (@pan-sec/notebooklm-mcp). Intercept sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Open source. One binary. Zero dependencies.
npx -y @policylayer/intercept