AI agents use source_sync 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.
Syncing pulls the latest content from Google Drive and updates the stored source in NotebookLM. This modifies the existing source's data, making it a Write operation. It is reversible in the sense that re-syncing or restoring old content could be possible, but it does overwrite the current source content. Severity is medium because misuse could cause unintended content updates across notebooks.
From the tool's definition 'Sync a Google Drive source to get the latest content' — synchronization implies updating/refreshing stored content from an external source
Documented attack patterns abuse exactly the kind of access source_sync 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 source_sync:
{
"version": "1",
"default": "deny",
"tools": {
"source_sync": {
"limits": [
{
"counter": "source_sync_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
}source_sync 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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Sync a Google Drive source to get the latest content. 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 source_sync: 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.
source_sync 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 source_sync 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 source_sync. 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.
source_sync 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.