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    "name": "youtube-transcript-scraper",
    "username": "fetch_cat",
    "description": "Extract transcripts and timestamped caption segments from public YouTube videos. Export text for summaries, RAG, content research, and AI-agent workflows.",
    "isPublic": true,
    "createdAt": "2026-06-14T14:59:04.102Z",
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    "exampleRunInput": {
      "body": "{\n  \"videoUrls\": [\n    \"https://www.youtube.com/watch?v=dQw4w9WgXcQ\"\n  ],\n  \"maxVideos\": 1,\n  \"language\": \"en\",\n  \"includeTimestamps\": true,\n  \"includeMetadata\": true\n}",
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    "categories": [
      "VIDEOS",
      "AI",
      "DEVELOPER_TOOLS"
    ],
    "isDeprecated": false,
    "title": "YouTube Transcript Scraper",
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    "seoTitle": "Extract YouTube Transcripts for AI & RAG",
    "seoDescription": "Extract public YouTube transcripts and timestamped caption segments for summaries, RAG, content research, SEO, and AI workflows. CSV, JSON, Excel, API.",
    "pricingInfos": [
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            "start": {
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            "transcript": {
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    "notice": "NONE",
    "isCritical": false,
    "isGeneric": false,
    "hasNoDataset": false,
    "isSourceCodeHidden": true,
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    "actorPermissionLevel": "LIMITED_PERMISSIONS",
    "readmeSummary": "## YouTube Transcript Scraper\n\nYouTube Transcript Scraper extracts and structures caption text from public YouTube videos into per-video records for transcript-based workflows. It converts YouTube caption tracks into clean full-text transcripts and optional timestamped segments, captures caption language and whether captions appear auto-generated, and includes available public video metadata such as title, channel, duration, and thumbnail. The Actor accepts common YouTube link formats and raw IDs, supports preferred caption-language selection with fallback behavior, and returns data optimized for text processing tasks like chunking, embedding, summarization, retrieval-augmented generation (RAG), quote extraction, and downstream AI-agent workflows.\n\n## Use cases\n\n- Repurpose video content into briefs, blog drafts, quote libraries, keyword research, and content audits for SEO and editorial teams.  \n- Collect spoken content for media monitoring, qualitative research, public-interest analysis, and education datasets.  \n- Produce clean text chunks for search, summarization, classification, embeddings, and retrieval/RAG pipelines for LLM applications.  \n- Extract talks, interviews, demos, webinars, and podcast-style episodes into searchable text for sales, marketing, and competitive review.  \n- Create searchable transcript records and quote tables to support journalism and fact-checking.  \n- Generate training data and corpora from public captions for machine learning and embedding-based search.  \n- Perform subtitle QA and language-availability checks across video collections.  \n- Automate summary and citation workflows (e.g., converting webinar captions into summaries with timestamps and notable quotes).",
    "deploymentKey": "ssh-rsa AAAAB3NzaC1yc2EAAAADAQABAAABAQDDxuosjzD2X0D5J82vIbQwrcUOl4hqwXZXTST4qTSpM/NYCErV2hEkidSnO5hfRGm3+mrl7Haiy37x0c9A8ldKmkXauJ7pHyQcFVX3vSjlfUfzHDK7pd0skK4TrIYSRSeZNjGjEnctrT/T/p+QOqYdk3/scVE/+wEHx/9X8wKc6ykTkCvJsg5ON6+/r1pxvhdc/+4CQLR7lCZP4Br0WcIBE7VXLeSi1c8kkX5Clj5rF8pLajuZTVlOxTYl2vsktLKRrACGFT5Ev+4x/QyOKToMC0HLPowL7FBT4+9ls96XT6q5r2udgBMmR38yqlG6vlPGFh2IVIaAX3G5ZgDo8jW9 \n"
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}