rippr
Drei Wege, rippr zu nutzen
🌐 Website — rippr.me
Füge eine YouTube-URL ein und erhalte das Transkript. Sauberer Text, keine Registrierung.
🧩 Chrome-Erweiterung — Chrome Web Store
Transkript-Extraktion mit einem Klick direkt auf jeder YouTube-Seite. Mehrere Ausgabeformate (RAG, JSON, Markdown).
🤖 MCP-Server — npm
Verbinde rippr mit Claude, Cursor oder einem beliebigen MCP-kompatiblen Client. Speichert jedes Transkript unter ~/rippr/transcripts/ und gibt den Dateipfad an das Modell zurück.
Nur Desktop-Clients. rippr läuft als lokaler stdio-Prozess und funktioniert daher mit Claude Desktop, Claude Code CLI und Cursor. Es funktioniert nicht mit Cloud-gehosteten Clients (claude.ai im Web, die Claude Mobile App oder Claude Code auf Telefon/Web), da diese keine lokalen Prozesse starten können.
npx rippr-mcpFüge dies zu Claude Desktop hinzu (~/Library/Application Support/Claude/claude_desktop_config.json):
{
"mcpServers": {
"rippr": {
"command": "npx",
"args": ["-y", "rippr-mcp"]
}
}
}Frage dann: "Rip this YouTube video: [url]". Siehe mcp/README.md für die vollständige Tool-Übersicht.
Related MCP server: xendit-mcp
Ausgabeformate
RAG (.txt) — einzelner zusammenhängender Textblock, optimiert für Chunking und Embedding
Strukturiert (.json) — zeitgestempelte Segmente mit Metadaten
Lesbar (.md) — Markdown mit Überschriften und Formatierung
Funktionsweise
Multi-Strategie-Extraktion für maximale Zuverlässigkeit:
Innertube API — YouTubes interne Player-API (Android-Client)
HTML-Scraping — parst
ytInitialPlayerResponseaus dem SeitenquelltextTranskript-Panel — öffnet als letzte Instanz das integrierte Transkript-Panel von YouTube
Caption-XML wird in mehreren Formaten geparst (srv3, timedtext, JSON3). Wiederholungsversuche mit exponentiellem Backoff bei vorübergehenden Fehlern.
Datenschutz
Läuft vollständig auf deinem Rechner. Keine Daten werden an externe Server gesendet. Keine Konten, kein Tracking. Kommuniziert ausschließlich mit den eigenen APIs von YouTube.
Weitere MCPs
MCP | Was es tut |
Japanische UX-Regeln für KI: Formulare, Keigo, Typografie, Vertrauenssignale | |
Durchsuche Rakutens Marktplatz, Bücher und Hotels | |
Xendit-Zahlungs-APIs: Rechnungen, Auszahlungen, Salden |
Haftungsausschluss
Rippr ist ein inoffizielles, von der Community entwickeltes Tool. Es ist nicht mit YouTube oder Google LLC verbunden, wird von diesen nicht unterstützt oder gesponsert. YouTube ist eine Marke von Google LLC.
Rippr greift über Endpunkte, die auch von YouTubes eigenen Apps verwendet werden, auf öffentlich verfügbare YouTube-Transkriptdaten zu. Die Nutzung unterliegt den Nutzungsbedingungen von YouTube und erfolgt auf eigene Gefahr. Der Autor übernimmt keine Haftung für Sperrungen, Ratenbegrenzungen, Kontoaktionen oder andere Folgen der Nutzung.
Sollte YouTube seine internen APIs so ändern, dass die Extraktion nicht mehr funktioniert, kann das Tool ohne Vorankündigung den Dienst einstellen. Für den langfristigen produktiven Einsatz ziehe bitte die offizielle YouTube Data API v3 mit einem API-Schlüssel in Betracht (wird derzeit von diesem Paket nicht unterstützt).
Lizenz
Available Tools
1 toolrip_transcriptA
Extract the full transcript from a YouTube video. By default, saves the transcript as a Markdown file to disk and returns a resource_link + metadata (title, channel, language, duration, word count, saved path, preview). The full transcript text is NOT returned by default — this keeps context lean and gives the user a persistent file they can reuse. After calling, always tell the user where the file was saved. If you need the transcript text later (summarize, search, extract quotes), read the returned resource rather than re-ripping. Pass return_text: true only for short clips or when the user explicitly asks for the transcript inline. Pass format: 'segments' to save timestamped JSON instead of Markdown.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | YouTube video URL. Supports any YouTube URL format (watch, youtu.be, embed, shorts, or bare 11-char ID). | |
| format | No | Saved file format. 'text' writes a Markdown file with YAML frontmatter and a continuous transcript block (best for RAG/LLM). 'segments' writes a JSON file with timestamped segments (best for chapter markers, precise citations). Default: text. | |
| save_path | No | Optional override for where to save the transcript. Can be an absolute path, a ~/-relative path, a directory (file is named automatically), or a full file path. When you save outside the default directory, the returned resource_link still points to the saved file so it can be read later. Default: ~/rippr/transcripts/<slug>_<videoId>.<ext> | |
| return_text | No | If true, include the full transcript text in the tool response alongside the resource_link. Default: false. Use true only for short clips or when the user explicitly wants the transcript inline. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Despite no annotations, the description fully discloses default behavior (saves file, does not return text), rationale (keep context lean, persistent file), and side effects (saves to disk). Could explicitly mention idempotency or rate limits, but overall strong.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Seven sentences, all contributing meaningful information. Front-loaded with purpose and key behavioral notes. No redundant or unnecessary content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers all critical aspects: default behavior, parameter usage, post-call action (tell user where saved). No output schema, but description is sufficient for agent to correctly invoke and follow up. Minor missing detail on resource_link format, but not essential.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, but description adds significant value: explains default behavior for format and return_text, supported URL formats, and save_path resolution details. Provides usage recommendations that go beyond schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description states 'Extract the full transcript from a YouTube video' with a specific verb and resource, clearly defining the tool's function. No sibling tools exist, so differentiation is not an issue.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit guidance: default saves file and returns metadata, advises against re-ripping by reading resource, specifies when to use return_text (short clips or explicit request) and format alternatives. Covers context and exclusions thoroughly.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
1 tool update
v0.1.0- Changed
rip_transcript4 fields changed- changed
Input schema / properties / format / descriptionPrevious value: -"Output format. 'text' returns a single continuous string (best for RAG/LLM). 'segments' returns timestamped segments. Default: text."New value: +"Saved file format. 'text' writes a Markdown file with YAML frontmatter and a continuous transcript block (best for RAG/LLM). 'segments' writes a JSON file with timestamped segments (best for chapter markers, precise citations). Default: text." - added
Input schema / properties / return_textAdded value: +{ + "description": "If true, include the full transcript text in the tool response alongside the resource_link. Default: false. Use true only for short clips or when the user explicitly wants the transcript inline.", + "type": "boolean" +} - added
Input schema / properties / save_pathAdded value: +{ + "description": "Optional override for where to save the transcript. Can be an absolute path, a ~/-relative path, a directory (file is named automatically), or a full file path. When you save outside the default directory, the returned resource_link still points to the saved file so it can be read later. Default: ~/rippr/transcripts/<slug>_<videoId>.<ext>", + "type": "string" +} - changed
Input schema / properties / url / descriptionPrevious value: -"YouTube video URL (e.g., https://www.youtube.com/watch?v=... or https://youtu.be/...)"New value: +"YouTube video URL. Supports any YouTube URL format (watch, youtu.be, embed, shorts, or bare 11-char ID)."
1 tool update
v1.0.0- First observed
rip_transcript
TDQS
Scored across 1 tool
With only one tool, there is no possibility of confusion. The single tool 'rip_transcript' has a clear and distinct purpose.
The single tool name 'rip_transcript' follows a consistent verb_noun pattern. No naming conflicts exist.
The server has only one tool, which is minimal but acceptable given its focused purpose of ripping YouTube transcripts. While slightly under-scoped, it provides a complete interface for its intended function.
The tool covers the core task of transcript extraction with options for format and inline text. However, it lacks complementary tools such as listing videos or batch processing, leaving minor gaps.
Maintenance
Related MCP Connectors
YouTube transcripts, video search, chapters and extractive summaries. No YouTube API key, no LLM.
YouTube transcripts for AI agents: text, JSON, SRT, or VTT in 150+ languages, with AI fallback.
Transcripts from YouTube videos, whole channels and playlists for AI agents, with bulk ZIP export.
YouTube transcripts for AI agents, including videos without captions (Pro API key).
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