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    "categories": [
      "SOCIAL_MEDIA",
      "VIDEOS"
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    "title": "YouTube Scraper",
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    "seoDescription": "Scrape YouTube video data, channel stats, and comments at scale. No-code YouTube scraper with easy setup. Export to JSON, CSV, Excel. AI-ready output.",
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    ],
    "notice": "NONE",
    "isCritical": false,
    "isGeneric": false,
    "hasNoDataset": false,
    "isSourceCodeHidden": true,
    "standbyUrl": null,
    "actorPermissionLevel": "LIMITED_PERMISSIONS",
    "readmeSummary": "## YouTube Scraper\n\nYouTube Scraper extracts structured YouTube data at scale by calling YouTube's internal InnerTube HTTP endpoints to collect search results, full video metadata, channel profiles, and video comments without requiring the YouTube Data API. It supports keyword search, per-video detail retrieval, channel catalog scraping, and comment extraction, following pagination for multi-page results; outputs include video attributes (titles, view counts, like counts, durations, descriptions, categories, keywords, publish dates), channel attributes (subscriber and video counts, verification status, descriptions, avatars/banners), and comment records (text, author info, likes, reply counts, hearted status, publish timestamps) suitable for SEO research, engagement analytics, sentiment/NLP pipelines, influencer and competitive analysis, and dataset generation.\n\n## Use cases\n\n- Market research: track video performance, trending topics, and competitor channels  \n- Brand monitoring: monitor mentions, comments, and engagement on relevant videos  \n- SEO research: analyze search results, keywords, title/description patterns, and ranking signals  \n- Content analysis: evaluate video metadata, engagement metrics, publishing cadence, and format trends  \n- Influencer analytics: gather channel statistics and content output for partnership decisions  \n- Competitive benchmarking: compare video performance across channels in a niche  \n- Sentiment analysis and NLP: extract comments for audience feedback and model training  \n- Academic and social research: collect structured YouTube data for studies and trend analysis  \n- Dataset building for ML: create labeled or unlabeled corpora from video metadata, descriptions, and comments",
    "deploymentKey": "ssh-rsa AAAAB3NzaC1yc2EAAAADAQABAAABAQDSrs34T2qVesgU6svkVqxUPZrVbs3thm6QI5xlTbA73bvDeJF23wsc+ptjyEFfaDzq3eMVnuvAVowL8nOz9cirKLu6MWmYw2k77IWrOWqHO6cR/XGfpzFN3VelLDaNAfjE+PvKDMsRJTojJYjYWyzkbnwAlPrCvajkJs3UDloM36YAg/MkUERedy9c29EFCrO9LwDeTKzin1domhmvx41BMv5bVgRrCS5GBwu1CbvpjyGnDON6dssLsXt7oKMkY1sqrUIIhtAwGtrhrln6HGWZvsBdWdDuoH+Q7/hg6XpBCmnFhNV0+okSTYLNSSnj/6GOssLmqF8lN9VTxEfHXtS9 \n"
  }
}