YouTube Transcript Scraper avatar

YouTube Transcript Scraper

Pricing

$5.00 / 1,000 transcript extracteds

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YouTube Transcript Scraper

YouTube Transcript Scraper

Extract YouTube video transcripts (captions, subtitles) in bulk as text or timestamped JSON. No API key. Auto-retries around YouTube bot blocks. Pay only for successful transcripts.

Pricing

$5.00 / 1,000 transcript extracteds

Rating

0.0

(0)

Developer

Guille Sanchez

Guille Sanchez

Maintained by Community

Actor stats

0

Bookmarked

2

Total users

1

Monthly active users

2 days ago

Last modified

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YouTube Transcript Scraper: captions and subtitles to text or JSON

Extract the transcript (captions, subtitles) of any YouTube video as clean text, with optional timestamped segments. Works in bulk: paste a list of video URLs or IDs and get one result per video. No YouTube API key needed.

Why use this one

  • Retries automatically. YouTube often blocks cloud IPs with "confirm you're not a bot". Each failed request is retried on a fresh IP session (up to 6 times) instead of failing your whole batch.
  • Pay only for results. You are charged per successfully extracted transcript. Videos without captions, private or removed videos are returned with an error field and cost nothing.
  • Language aware. Pick a language (en, es, de, ...). Falls back to the closest available track and tells you whether captions are auto-generated.
  • Any link format. watch URLs, youtu.be short links, Shorts, embeds, or bare 11-character video IDs.

Input

FieldDescription
videosList of YouTube URLs or video IDs
languagePreferred caption language code, default en
includeSegmentsAdd start, duration, text for each caption line
proxyConfigurationResidential proxy recommended (default)

Output example

{
"videoId": "dQw4w9WgXcQ",
"title": "Rick Astley - Never Gonna Give You Up",
"channel": "Rick Astley",
"language": "en",
"isAutoGenerated": false,
"availableLanguages": ["en", "de-DE", "ja"],
"text": "We're no strangers to love ...",
"segments": [{ "start": 18.4, "duration": 3.2, "text": "We're no strangers to love" }]
}

Typical uses

Feed transcripts to an LLM or RAG pipeline, summarize videos, build search over video archives, research and content repurposing, subtitle datasets.

Only publicly available captions are extracted. Respect the rights of video owners and YouTube's terms when using the output.