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notebooklm-skill

von claude-world · claude-world/notebooklm-skill

NotebookLM researches with citations, Claude writes the content — a four-phase Collect → Research → Generate → Publish workflow.

NotebookLM Skill bridges Google's NotebookLM research environment with Claude's content generation. You feed URLs/PDFs/YouTube into a notebook, NotebookLM extracts cited insights, and Claude drafts articles, social posts, newsletters, or custom formats. Works as a Claude Code skill or standalone MCP server. Browser-based Google auth — no API keys.

▶ Demo ansehen 📦 Installieren 💡 Anwendungsfälle

Warum nutzen

Hauptfunktionen

Live-Demo

In der Praxis

notebooklm-skill.replay ▶ bereit
0/0

Installieren

Wählen Sie Ihren Client

~/Library/Application Support/Claude/claude_desktop_config.json  · Windows: %APPDATA%\Claude\claude_desktop_config.json
{
  "mcpServers": {
    "notebooklm-skill": {
      "command": "git",
      "args": [
        "clone",
        "https://github.com/claude-world/notebooklm-skill",
        "~/.claude/skills/notebooklm-skill"
      ],
      "_inferred": true
    }
  }
}

Öffne Claude Desktop → Settings → Developer → Edit Config. Nach dem Speichern neu starten.

~/.cursor/mcp.json · .cursor/mcp.json
{
  "mcpServers": {
    "notebooklm-skill": {
      "command": "git",
      "args": [
        "clone",
        "https://github.com/claude-world/notebooklm-skill",
        "~/.claude/skills/notebooklm-skill"
      ],
      "_inferred": true
    }
  }
}

Cursor nutzt das gleiche mcpServers-Schema wie Claude Desktop. Projektkonfiguration schlägt die globale.

VS Code → Cline → MCP Servers → Edit
{
  "mcpServers": {
    "notebooklm-skill": {
      "command": "git",
      "args": [
        "clone",
        "https://github.com/claude-world/notebooklm-skill",
        "~/.claude/skills/notebooklm-skill"
      ],
      "_inferred": true
    }
  }
}

Klicken Sie auf das MCP-Servers-Symbol in der Cline-Seitenleiste, dann "Edit Configuration".

~/.codeium/windsurf/mcp_config.json
{
  "mcpServers": {
    "notebooklm-skill": {
      "command": "git",
      "args": [
        "clone",
        "https://github.com/claude-world/notebooklm-skill",
        "~/.claude/skills/notebooklm-skill"
      ],
      "_inferred": true
    }
  }
}

Gleiche Struktur wie Claude Desktop. Windsurf neu starten zum Übernehmen.

~/.continue/config.json
{
  "mcpServers": [
    {
      "name": "notebooklm-skill",
      "command": "git",
      "args": [
        "clone",
        "https://github.com/claude-world/notebooklm-skill",
        "~/.claude/skills/notebooklm-skill"
      ]
    }
  ]
}

Continue nutzt ein Array von Serverobjekten statt einer Map.

~/.config/zed/settings.json
{
  "context_servers": {
    "notebooklm-skill": {
      "command": {
        "path": "git",
        "args": [
          "clone",
          "https://github.com/claude-world/notebooklm-skill",
          "~/.claude/skills/notebooklm-skill"
        ]
      }
    }
  }
}

In context_servers hinzufügen. Zed lädt beim Speichern neu.

claude mcp add notebooklm-skill -- git clone https://github.com/claude-world/notebooklm-skill ~/.claude/skills/notebooklm-skill

Einzeiler. Prüfen mit claude mcp list. Entfernen mit claude mcp remove.

Anwendungsfälle

Praxisnahe Nutzung: notebooklm-skill

How to turn a stack of sources into a researched, cited article

👤 Content marketers and technical writers publishing researched longform ⏱ ~45 min intermediate

Wann einsetzen: You have 5-20 URLs and PDFs on a topic and need a polished article with citations in under an hour.

Voraussetzungen
  • Python 3.10+ — pyenv install 3.10 or system python3
  • Google account with NotebookLM access — Sign in at notebooklm.google.com once; browser session is reused
  • notebooklm-py library — pip install notebooklm-py
Ablauf
  1. Collect sources into a notebook
    Create a notebook titled 'CRDT-landscape-2026' and add these 8 URLs and this PDF.✓ Kopiert
    → Notebook ID returned; source count confirmed
  2. Run research queries
    Ask the notebook: 'What are the main CRDT types and their tradeoffs? Cite each claim.'✓ Kopiert
    → Structured answer with inline citations to specific sources
  3. Generate an article
    Using those findings, draft a 1500-word article for a backend audience. Keep citations as footnotes.✓ Kopiert
    → Draft with [n] citation markers keyed to source URLs
  4. Publish
    Save to drafts/crdt-landscape.md with frontmatter (title, date, tags).✓ Kopiert
    → Markdown file on disk

Ergebnis: A cited, publishable draft grounded in specific sources — not hallucinated.

Fallstricke
  • Browser auth expires silently — Re-open notebooklm.google.com and refresh; skill reuses the cookie jar
  • Claude paraphrases a claim without its citation — Explicitly instruct: 'Every factual sentence must end with its [n] citation.'
Kombinieren mit: smart-illustrator-skill

Turn research sources into a podcast-style audio overview

👤 Podcasters and educators who want an audio summary from reading material ⏱ ~15 min beginner

Wann einsetzen: You want NotebookLM's Audio Overview feature triggered from your agent instead of the web UI.

Ablauf
  1. Add sources and request audio
    Create notebook from these 6 papers, then trigger audio overview.✓ Kopiert
    → Audio generation kicked off; status returned
  2. Poll and download
    Wait for audio, then save as overview.mp3 in my downloads.✓ Kopiert
    → Local MP3 file

Ergebnis: A downloaded audio overview without opening the NotebookLM web UI.

Fallstricke
  • Audio takes 2-5 minutes to render — Use the polling flow; don't expect sync completion

Repurpose one notebook into a week of social posts

👤 Founders and solo marketers spreading one piece of research across channels ⏱ ~30 min beginner

Wann einsetzen: You just finished a deep-dive notebook and want 7 LinkedIn posts + 5 tweets from it.

Ablauf
  1. Extract hooks
    From notebook 'CRDT-landscape-2026', list the 12 most share-worthy specific facts with source citations.✓ Kopiert
    → Bullet list of cited hooks
  2. Draft posts
    Turn each hook into a LinkedIn post (200-280 words) and a tweet (under 280 chars). Keep citations as links.✓ Kopiert
    → Post-and-tweet pairs per hook

Ergebnis: A scheduled week of cited social content.

Fallstricke
  • Social drafts sound generic — Feed Claude 3 of your past posts for voice before drafting
Kombinieren mit: ai-marketing-claude-code-skill

Kombinationen

Mit anderen MCPs für 10-fache Wirkung

notebooklm-skill + smart-illustrator-skill

NotebookLM research → Claude drafts → Smart Illustrator adds diagrams

Research 'vector DB landscape' with notebooklm, draft a 2000-word article, illustrate with smart-illustrator.✓ Kopiert
notebooklm-skill + ai-marketing-claude-code-skill

Turn researched content into marketing campaigns with real citations

Take findings from notebook XYZ and run the go-to-market skill to produce a launch plan with cited claims.✓ Kopiert
notebooklm-skill + claude-skills-journalism-skill

Journalism workflows that demand source verification

Use notebooklm to verify each claim in this draft against the uploaded primary sources before publishing.✓ Kopiert

Werkzeuge

Was dieses MCP bereitstellt

WerkzeugEingabenWann aufrufenKosten
create_notebook title: str, sources: list[url|pdf|youtube] First step of any research task NotebookLM free quota
add_sources notebook_id, sources Extend existing notebook free
ask notebook_id, question Primary research interaction NotebookLM free quota
generate_audio_overview notebook_id, style? When you want the podcast-style overview free, async
export_artifacts notebook_id, type: 'slides'|'report'|'quiz'|'flashcards' Repurposing research into other formats free

Kosten & Limits

Was der Betrieb kostet

API-Kontingent
NotebookLM free tier is generous but unpublished. Heavy use may trigger rate limiting.
Tokens pro Aufruf
Research answers use Google's quota; Claude token use depends on drafting length
Kosten in €
Free with a Google account
Tipp
Batch multiple questions per notebook session — avoid re-uploading sources across notebooks.

Sicherheit

Rechte, Secrets, Reichweite

Credential-Speicherung: Browser cookie session for Google. No API keys. Session stored in notebooklm-py's local cache.
Datenabfluss: All source content is uploaded to NotebookLM (Google). Don't feed confidential material.

Fehlerbehebung

Häufige Fehler und Lösungen

Auth failed / 'please sign in'

Open notebooklm.google.com in your default browser, sign in, then retry. Skill reuses the browser cookie jar.

Prüfen: python -c 'import notebooklm_py; print(notebooklm_py.whoami())'
Source rejected as unsupported

NotebookLM accepts specific formats. Convert PDFs to text or host as public URL if needed.

Audio overview stuck in 'pending'

Normal — takes 2-5 min. Poll with export status.

Alternativen

notebooklm-skill vs. andere

AlternativeWann stattdessenKompromiss
Manual web-search + summarizeYou don't have a Google account or need air-gapped workflowNo citation grounding; higher hallucination risk
Perplexity APIYou want a paid API with SLAsCosts money, but more reliable than browser automation

Mehr

Ressourcen

📖 Offizielle README auf GitHub lesen

🐙 Offene Issues ansehen

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