NotebookLM MCP Server
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- AlicenseAqualityFmaintenanceEnables interaction with Google's NotebookLM through natural language to create and manage notebooks, add sources from URLs/YouTube/Drive, perform AI-powered research and analysis, and generate audio overviews, videos, infographics, and slide decks from research content.326MIT
- AlicenseAqualityNot gradedmaintenanceEnables interaction with Google's NotebookLM through natural language, allowing users to create and manage notebooks, add sources from URLs/YouTube/Google Drive, query AI for insights, generate audio podcasts and other studio content, and perform AI-powered research and analysis.323MIT
- AlicenseNot gradedqualityBmaintenanceEnables AI assistants to manage Google NotebookLM notebooks, add sources from URLs, YouTube, Drive, or text, query and summarize content, and generate audio overviews, infographics, and slide decks through natural language.MIT
- AlicenseBqualityAmaintenanceEnables AI assistants to programmatically interact with Google NotebookLM, allowing them to create and manage notebooks, add sources, query content, generate audio/video, and perform research tasks through natural language commands.4912,935 PyPI6,145MIT
- AlicenseNot gradedqualityDmaintenanceEnables interaction with Google NotebookLM to create notebooks, add sources (PDF, URL, YouTube), and ask questions with citations.1MIT
- AlicenseAqualityDmaintenanceEnables AI assistants to programmatically access and control Google NotebookLM, supporting operations like notebook management, source addition, audio generation, and more via natural language.39MIT
TDQS
Scored across 32 tools
Most tools have distinct purposes targeting specific notebook operations (e.g., audio_overview_create vs. video_overview_create, notebook_add_drive vs. notebook_add_text). However, some potential confusion exists between notebook_query (querying existing sources) and research_start (finding new sources), though descriptions clarify this distinction. The various 'create' tools for different content types (flashcards, infographic, mind_map, etc.) are well-differentiated by their output formats.
Tool names follow a highly consistent snake_case pattern with clear verb_noun structure throughout (e.g., notebook_create, notebook_list, source_delete, research_start). The naming convention is uniform across all 32 tools, making them predictable and easy to parse. Even complex operations like save_auth_tokens and studio_status maintain this consistent pattern.
With 32 tools, the count feels heavy for a notebook management server, though the domain is broad (notebook CRUD, source management, content generation, research). While many tools are justified (e.g., different content creation types), the number approaches the upper limit of what's manageable. A more streamlined set might combine some similar creation tools or reduce redundancy in source management operations.
The tool surface provides comprehensive coverage of the notebook management domain. It includes full CRUD for notebooks and sources, multiple content generation options (audio, video, reports, quizzes, etc.), research workflows with start/status/import tools, and administrative functions like authentication and synchronization. There are no apparent gaps - agents can perform complete notebook lifecycles from creation through content generation to deletion.