Configure notebook chat settings (goal, response length)
AI agents use chat_configure 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 settings in a reversible manner. Changing chat configuration (goal, response length) is a Write operation because it updates notebook state, but the changes are non-destructive and can be reverted. There is no deletion, irreversible loss, code execution, or financial impact.
From the tool's definition Tool is described as 'Configure notebook chat settings (goal, response length)' — it modifies configuration parameters for a notebook chat interface.
Documented attack patterns abuse exactly the kind of access chat_configure 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 chat_configure:
{
"version": "1",
"default": "deny",
"tools": {
"chat_configure": {
"limits": [
{
"counter": "chat_configure_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
}chat_configure 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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Configure notebook chat settings (goal, response length). 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 chat_configure: 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.
chat_configure 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 chat_configure 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 chat_configure. 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.
chat_configure 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.