rippr
Tres formas de usar rippr
🌐 Sitio web — rippr.me
Pega una URL de YouTube y obtén la transcripción. Texto limpio, sin registro.
🧩 Extensión de Chrome — Chrome Web Store
Extracción de transcripciones con un solo clic directamente en cualquier página de YouTube. Múltiples formatos de salida (RAG, JSON, Markdown).
🤖 Servidor MCP — npm
Conecta rippr a Claude, Cursor o cualquier cliente compatible con MCP. Guarda cada transcripción en ~/rippr/transcripts/ y devuelve la ruta del archivo al modelo.
Solo clientes de escritorio. rippr se ejecuta como un proceso local stdio, por lo que funciona con Claude Desktop, Claude Code CLI y Cursor. No funciona con clientes alojados en la nube (claude.ai en la web, la aplicación móvil de Claude o Claude Code en teléfono/web), que no pueden generar procesos locales.
npx rippr-mcpAñádelo a Claude Desktop (~/Library/Application Support/Claude/claude_desktop_config.json):
{
"mcpServers": {
"rippr": {
"command": "npx",
"args": ["-y", "rippr-mcp"]
}
}
}Luego pregunta: "Rip this YouTube video: [url]". Consulta mcp/README.md para ver la interfaz completa de la herramienta.
Related MCP server: xendit-mcp
Formatos de salida
RAG (.txt) — bloque de texto continuo único, optimizado para fragmentación (chunking) e incrustación (embedding)
Estructurado (.json) — segmentos con marca de tiempo y metadatos
Legible (.md) — markdown con encabezados y formato
Cómo funciona
Extracción con múltiples estrategias para una máxima fiabilidad:
Innertube API — API interna del reproductor de YouTube (cliente Android)
Web scraping — analiza
ytInitialPlayerResponsedesde el código fuente de la páginaPanel de transcripción — abre el panel de transcripción integrado de YouTube como último recurso
XML de subtítulos analizado en múltiples formatos (srv3, timedtext, JSON3). Reintento con retroceso exponencial ante fallos transitorios.
Privacidad
Se ejecuta completamente en tu máquina. No se envían datos a servidores externos. Sin cuentas, sin seguimiento. Solo se comunica con las propias APIs de YouTube.
Más MCPs
MCP | Qué hace |
Reglas de UX japonesa para IA: formularios, keigo, tipografía, señales de confianza | |
Busca en el mercado, libros y hoteles de Rakuten | |
APIs de pago de Xendit: facturas, desembolsos, saldos |
Aviso legal
Rippr es una herramienta no oficial creada por la comunidad. No está afiliada, respaldada ni patrocinada por YouTube o Google LLC. YouTube es una marca comercial de Google LLC.
Rippr accede a datos de transcripción de YouTube disponibles públicamente a través de endpoints que utilizan las propias aplicaciones de YouTube. El uso está sujeto a los Términos de servicio de YouTube y se realiza bajo tu propia responsabilidad. El autor no acepta ninguna responsabilidad por eliminaciones, límites de tasa, acciones de cuenta o cualquier otra consecuencia del uso.
Si YouTube cambia sus APIs internas de forma que interrumpa la extracción, la herramienta puede dejar de funcionar sin previo aviso. Para un uso en producción a largo plazo, considera la YouTube Data API v3 oficial con una clave API (actualmente no compatible con este paquete).
Licencia
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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- AlicenseAqualityDmaintenanceEnables AI assistants to fetch YouTube video transcripts with precise timestamps, multi-language support, and time-range filtering.31MIT