YouTubeのURLを貼り付けるだけで、文字起こしを取得できます。クリーンなテキストで、登録も不要です。
YouTubeページ上でワンクリックで文字起こしを抽出。複数の出力形式（RAG、JSON、Markdown）に対応しています。
ripprをClaude、Cursor、またはMCP対応クライアントに接続します。各文字起こしを ~/rippr/transcripts/ に保存し、モデルにファイルパスを返します。
デスクトップクライアント専用。 ripprはローカルのstdioプロセスとして実行されるため、Claude Desktop、Claude Code CLI、Cursorで動作します。クラウドホスト型のクライアント（ウェブ版claude.ai、Claudeモバイルアプリ、または電話/ウェブ上のClaude Code）では、ローカルプロセスを起動できないため動作しません。
npx rippr-mcpClaude Desktopに追加します (~/Library/Application Support/Claude/claude_desktop_config.json):
{
"mcpServers": {
"rippr": {
"command": "npx",
"args": ["-y", "rippr-mcp"]
}
}
}その後、"Rip this YouTube video: [url]" と尋ねてください。ツールの全機能については mcp/README.md を参照してください。
Related MCP server: YouTube Transcript MCP
RAG (.txt) — チャンク化や埋め込みに最適化された、単一の連続したテキストブロック
構造化 (.json) — メタデータ付きのタイムスタンプ付きセグメント
可読性重視 (.md) — 見出しとフォーマット付きのMarkdown
信頼性を最大化するためのマルチ戦略抽出:
Innertube API — YouTubeの内部プレイヤーAPI（Androidクライアント）
HTMLスクレイピング — ページソースから ytInitialPlayerResponse を解析
文字起こしパネル — 最終手段としてYouTubeの内蔵文字起こしパネルを開く
キャプションXMLは複数の形式（srv3、timedtext、JSON3）で解析されます。一時的な障害が発生した場合は、指数バックオフで再試行します。
すべてお使いのPC上で実行されます。外部サーバーへのデータ送信はありません。アカウント登録や追跡もありません。YouTube自身のAPIとのみ通信します。
MCP | 説明 |
AIのための日本のUXルール：フォーム、敬語、タイポグラフィ、信頼シグナル | |
楽天のマーケットプレイス、書籍、ホテルの検索 | |
Xendit決済API：請求書、支払い、残高 |
Ripprは非公式のコミュニティ製ツールです。YouTubeやGoogle LLCと提携、推奨、後援されているものではありません。YouTubeはGoogle LLCの商標です。
Ripprは、YouTube自身のアプリが使用するエンドポイントを通じて、公開されているYouTubeの文字起こしデータにアクセスします。利用はYouTubeの利用規約に従うものとし、自己責任で行ってください。著者は、削除、レート制限、アカウントへの措置、またはその他の利用結果について一切の責任を負いません。
YouTubeが内部APIを変更し、抽出が機能しなくなった場合、予告なくツールが動作しなくなる可能性があります。長期的な本番環境での利用については、APIキーを使用した公式の YouTube Data API v3 の利用を検討してください（本パッケージでは現在サポートされていません）。
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. |
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.
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.
Unclaimed servers have limited discoverability.
If you are the server author, to access and configure the admin panel.
YouTube transcripts, search, channel/playlist listings and upload tracking for AI agents. No signup.
Fetch the full transcript of any YouTube video as clean text. No API key, no signup.
Clean YouTube transcripts for agents: single videos, channels, playlists, plus AI caption cleanup.
Any video URL to LLM-ready transcript. ASR built in, no captions needed. TikTok, X, TED and more.
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