How to Export YouTube Transcripts and Video Metadata Automatically

YouTube has 800 million videos and generates over 500 hours of new content every minute. For researchers, content creators, and AI developers, that’s an extraordinary corpus of structured information — titles, descriptions, metadata, transcripts, comments.

Getting at it systematically is where the friction starts.

The problem with YouTube’s official API

YouTube Data API v3 exists and is actually usable — but it has limitations:

• Quota: 10,000 units/day by default (a channel list request costs 1 unit, a video details request costs 1–3, a search costs 100)
• Transcripts: not available via the official API at all
• Comments: available but paginated and rate-limited
• Raising quota requires manual review and can take weeks

For bulk enrichment, competitive research, or AI training data, you’ll hit the wall fast.

What YouTube workers extract

From a video:

• Title, description, duration, publish date
• View count, like count, comment count
• Channel name, channel ID, subscriber count
• Tags, category, language
• Transcript (full, timestamped, or plain text)

From a channel:

• All videos (up to a specified limit)
• Subscriber count, total views, video count
• Channel description, links, creation date

From a search query:

• Top N videos matching the query
• All metadata fields above for each result

Extracting a transcript

curl -X POST https://api.seek-api.com/v1/workers/youtube-transcript/jobs \
  -H "X-Api-Key: YOUR_KEY" \
  -H "Content-Type: application/json" \
  -d '{"videoUrl": "https://www.youtube.com/watch?v=dQw4w9WgXcQ", "format": "plain"}'

Response:

{
  "videoId": "dQw4w9WgXcQ",
  "title": "Rick Astley...",
  "duration": 212,
  "transcript": "We're no strangers to love. You know the rules and so do I...",
  "language": "en",
  "segments": [
    {"start": 0.0, "end": 3.4, "text": "We're no strangers to love."},
    {"start": 3.4, "end": 6.1, "text": "You know the rules and so do I."}
  ]
}

Set "format": "segments" to get the full timestamped array for subtitle-style output.

AI use cases for transcripts

Once you have transcripts, the possibilities are wide:

Summarization: Feed the transcript to GPT-4o and extract a 3-sentence summary for a newsletter or content digest.

Q&A extraction: Parse transcripts of tutorial videos to build FAQ databases or knowledge bases.

Training data: Collect domain-specific transcripts (legal, medical, technical) to fine-tune models.

Keyword mining: Identify recurring phrases and topics across a channel to find what resonates with an audience.

Multilingual content: Detect transcript language, translate, and republish in new markets.

Channel analysis pipeline

Analyze a competitor’s full YouTube channel:

import httpx, time

VIDEO_LIMIT = 50

# Step 1: Get all videos
job = httpx.post(
    "https://api.seek-api.com/v1/workers/youtube-channel/jobs",
    headers={"X-Api-Key": API_KEY},
    json={"channelUrl": "https://www.youtube.com/@MrBeast", "limit": VIDEO_LIMIT}
).json()

# Wait for result
while True:
    status = httpx.get(f"https://api.seek-api.com/v1/jobs/{job['job_uuid']}", headers=...).json()
    if status["status"] == "completed":
        videos = status["result"]["videos"]
        break
    time.sleep(5)

# Step 2: Get transcripts for all videos
transcript_jobs = []
for v in videos:
    j = httpx.post(
        "https://api.seek-api.com/v1/workers/youtube-transcript/jobs",
        headers={"X-Api-Key": API_KEY},
        json={"videoUrl": v["url"]}
    ).json()
    transcript_jobs.append(j["job_uuid"])

In one pipeline, you now have 50 transcripts from a competitor channel — structured, searchable, ready for any downstream analysis.

Comment extraction for sentiment analysis

YouTube comments are a goldmine for product feedback, audience opinion, and social listening:

POST /v1/workers/youtube-comments/jobs
{
  "videoUrl": "https://www.youtube.com/watch?v=...",
  "limit": 200,
  "sort": "top"
}

Feed the top 200 comments into a sentiment classifier to instantly understand how a piece of content was received.

Cost breakdown

A complete competitive analysis of a rival’s top 50 videos costs about 13 cents.