YouTube Transcript & Captions Scraper 🎬

Extract fast, clean, and complete YouTube video transcripts with timestamps, text, token counts, and video metadata in seconds. Designed specifically for AI agents, LLM ingestion, automated video summarization, and RAG pipelines.

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What does YouTube Transcript Scraper do?

YouTube Transcript Scraper extracts transcripts and closed captions from any public YouTube video, YouTube Short, or Video ID:

• Clean Full Transcript: Continuous plain-text transcript stripped of formatting, ready for LLMs.
• Timestamped Segments: Start time, duration, and text for every caption segment.
• Video Metadata: Title, channel name, channel URL, and high-res thumbnail URL.
• LLM Token Estimation: Pre-computed character and token counts for context planning.
• Lightning Fast: Pure HTTP extraction (sub-second per video), zero heavy browser overhead.

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Why use YouTube Transcript Scraper?

• AI Summarization & RAG: Feed YouTube video transcripts directly into ChatGPT, Claude, LangChain, or vector databases.
• Content Repurposing: Turn YouTube videos into blog posts, newsletters, Twitter/X threads, or LinkedIn posts.
• Pay Per Event (PPE): Ultra-cheap micropayment per video transcribed ($0.002 per video), avoiding expensive subscriptions.
• Support Shorts & Long Videos: Works with standard videos and YouTube Shorts alike.

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How to use

1. Enter one or more YouTube Video URLs or IDs (one per line).
2. Toggle whether to include timestamped segments.
3. Click Start to run the scraper.
4. Download your transcripts in JSON, CSV, or Excel format.

Input Example

{
  "videoUrls": [
    "https://www.youtube.com/watch?v=jNQXAC9IVRw",
    "https://youtu.be/dQw4w9WgXcQ"
  ],
  "includeTimestamps": true
}

Output Example

{
  "videoId": "jNQXAC9IVRw",
  "videoUrl": "https://www.youtube.com/watch?v=jNQXAC9IVRw",
  "title": "Me at the zoo",
  "channelName": "jawed",
  "channelUrl": "https://www.youtube.com/@jawed",
  "thumbnailUrl": "https://i.ytimg.com/vi/jNQXAC9IVRw/hqdefault.jpg",
  "fullText": "All right, so here we are, in front of the elephants. The cool thing about these guys is that they have really really long trunks...",
  "segmentsCount": 6,
  "characterCount": 146,
  "estimatedTokens": 36,
  "segments": [
    { "start": 1.2, "duration": 2.16, "text": "All right, so here we are, in front of the elephants" },
    { "start": 5.32, "duration": 2.66, "text": "the cool thing about these guys is that they have really..." }
  ],
  "elapsedMs": 320,
  "status": "success"
}

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Extracted Fields

Field	Type	Description
videoId	string	11-character YouTube video ID
title	string	Official video title
channelName	string	Creator channel name
channelUrl	string	URL of the YouTube channel
thumbnailUrl	string	High quality video thumbnail link
fullText	string	Clean consolidated transcript text
estimatedTokens	integer	Estimated LLM token count (~chars/4)
segments	array	Timestamped caption blocks with start time and duration
status	string	success or error

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API Integration

from apify_client import ApifyClient

client = ApifyClient("YOUR_APIFY_TOKEN")
run = client.actor("drain54/youtube-transcript-scraper").call(
    run_input={"videoUrls": ["https://www.youtube.com/watch?v=jNQXAC9IVRw"]}
)

for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item["title"])
    print(item["fullText"])