youtube transcript fetcher avatar
youtube transcript fetcher

Pricing

Pay per usage

Go to Apify Store
youtube transcript fetcher

youtube transcript fetcher

Extracts the full transcript text from a YouTube video by automatically opening the transcript panel and collecting all spoken segments. The transcript is saved as plain text in the actor’s dataset for easy analysis, search, or AI processing.

Pricing

Pay per usage

Rating

0.0

(0)

Developer

Arron Taylor

Arron Taylor

Maintained by Community

Actor stats

0

Bookmarked

5

Total users

3

Monthly active users

3 days ago

Last modified

Categories

Share

YouTube Transcript Extractor

This actor extracts the full transcript text from a YouTube video.

Given a YouTube video URL, it automatically opens the video’s transcript panel and collects all spoken segments into a single plain-text transcript, which is saved to the actor’s dataset.

This is useful for summarization, search indexing, AI analysis, or archiving spoken content from YouTube videos.

How it works

For a given YouTube video URL, the actor: 1. Opens the video page 2. Expands the video description if needed 3. Finds and clicks the “Show transcript” button 4. Waits for the transcript panel to load 5. Extracts all transcript segments 6. Combines them into one text output 7. Saves the transcript to the dataset

Input

{ "startUrls": [ { "url": "https://www.youtube.com/watch?v=VIDEO_ID" } ], "proxyConfig": {} }

Input fields • startUrls – List of YouTube video URLs to process (only the first URL is used) • proxyConfig – Optional proxy configuration

Output

The actor stores results in the default dataset.

Each dataset item contains:

{ "transcript": "Full transcript text from the video..." }

• Transcript text is returned as a single combined string
• Timestamps are not included

Notes & limitations • Only works for videos where YouTube transcripts are available • Processes one video per run • Does not include timestamps or speaker labels • Relies on YouTube’s current interface, which may change over time