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by claude-world • Uncategorized
An MCP server that integrates NotebookLM research with Claude AI for content creation and multi-platform publishing.
Automate deep research and content generation from web sources and trending topics.
Create multi-format artifacts like podcasts, slides, and reports from research data.
Integration with MCP-compatible clients and Claude Code for streamlined AI workflows.
notebooklm-skill enables automated research by ingesting URLs, PDFs, and trending topics to create NotebookLM notebooks, perform deep research queries, and generate structured findings. It then uses Claude to produce polished content such as articles, social posts, newsletters, podcasts, and more. The tool supports artifact generation including audio, video, slides, reports, quizzes, and infographics, facilitating seamless multi-format publishing workflows.
Create a NotebookLM notebook, optionally with URL and text sources. Args: title: Human-readable notebook title. sources: Optional list of URLs to ingest (web pages, PDFs, YouTube). text_sources: Optional list of raw text strings to add as sources. Returns: Notebook metadata including notebook id and sources added. Example: nlm_create_notebook( title="AI Safety Research", sources=["https://arxiv.org/abs/2401.00001"], text_sources=["Additional context about AI alignment..."] )
List all notebooks in the NotebookLM account. Returns: Dict with notebooks list, each containing id and title. Example: nlm_list()
Delete a notebook and all its sources. Irreversible. Args: notebook: Notebook ID or title to delete. Returns: Deletion status and deleted notebook ID. Example: nlm_delete(notebook="Old Research")
Add a source to an existing notebook. Provide exactly one of: url, text, or file_path. Args: notebook: Notebook ID or title. url: URL to add (web page, PDF, YouTube, etc.). text: Raw text content to add as a source. text_title: Title for the text source (default "Text Source"). file_path: Local file path to upload (PDF, TXT, etc.). Returns: Source metadata including source id and type. Example: nlm_add_source(notebook="My Research", url="https://example.com/paper.pdf") nlm_add_source(notebook="My Research", text="Key finding: ...", text_title="Notes")
Ask a question against a notebook's ingested sources. The answer is grounded in the notebook's content and includes citations. Args: notebook: Notebook ID or title to query. query: Natural-language question. Returns: Answer text with citations pointing to source passages. Example: nlm_ask(notebook="AI Safety Research", query="What are the main risks?")
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