What problem does it solve?
It solves the problem of configuring authenticated access to your private NotebookLM content through an MCP server, so you can query and use NotebookLM data from your AI agent workflow without manual reconfiguration.
Core Features & Use Cases
- MCP server setup guidance: Installs and wires the Python-based NotebookLM MCP server into your agent via
mcp_config.json.
- Authentication methods: Provides both an automatic cookie-extraction approach and a manual cookie/token extraction fallback to handle common 403/handshake issues.
- Validation workflow: Includes a quick Python verification routine to confirm tokens are cached and notebooks can be listed.
Use case example: You want your agent (Claude/Cursor/Antigravity or any compatible MCP client) to list your notebooks and answer questions grounded in your NotebookLM collections.
Quick Start
Install the Skill and then run the authentication step (preferably notebooklm-mcp-auth) followed by configuring your mcp_config.json to launch notebooklm-mcp.