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YouTube Video Subtitles Scraper With Keyword Search

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YouTube Video Subtitles Scraper extracts captions, subtitles, video titles, channels, and metadata from YouTube videos. Search by keywords to find relevant videos and collect subtitle data for content research, SEO, transcription, and analysis.

Pricing

from $4.99 / 1,000 results

Rating

0.0

(0)

Developer

API Empire

Actor stats

Bookmarked

Total users

Monthly active users

3 days ago

Last modified

Categories

Videos

Lead generation

Automation

You can access the YouTube Video Subtitles Scraper With Keyword Search programmatically from your own applications by using the Apify API. You can also choose the language preference from below. To use the Apify API, you’ll need an Apify account and your API token, found in API & Integrations in Apify Console.

Python

JavaScript

CLI

OpenAPI

HTTP

MCP

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            "items": {
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          "preferredCaptionLanguage": {
            "title": "🌍 Preferred Caption Language",
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            "description": "Language code to prefer when a video has more than one caption track (examples: 'en' English, 'es' Spanish, 'fr' French). If the video has no track in this language, the actor falls back to the best available track automatically. Default is 'en'."
          },
          "language": {
            "title": "🗣️ Language (legacy key)",
            "type": "string",
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            "default": "en"
          },
          "maxWorkers": {
            "title": "⚙️ Maximum Concurrent Workers",
            "minimum": 1,
            "maximum": 10,
            "type": "integer",
            "description": "Number of videos processed in parallel (1-10). Higher values finish a batch faster. Default is 4.",
            "default": 4
          },
          "searchKeywords": {
            "title": "🔎 Keywords / Phrases To Find",
            "type": "array",
            "description": "One keyword or phrase per line to search for inside every video's transcript (e.g. 'never', 'give you up'). Leave empty to skip the search and only fetch the transcript. Example: searchKeywords=['never','up'] on a video whose transcript repeats 'never' 5 times -> 5 matches, each with its own timestamp and https://youtu.be/<id>?t=<seconds> link.",
            "items": {
              "type": "string"
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          },
          "caseSensitiveSearch": {
            "title": "🔠 Case-Sensitive Search",
            "type": "boolean",
            "description": "When on, 'Music' and 'music' are treated as different keywords. Default is off (case-insensitive).",
            "default": false
          },
          "wholeWordOnly": {
            "title": "🧩 Whole Word / Phrase Only",
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            "description": "When on, 'cat' will not match inside 'category'. Default is off (substring matching allowed).",
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          },
          "contextWindowSeconds": {
            "title": "⏱️ Context Window (seconds)",
            "minimum": 0,
            "maximum": 120,
            "type": "integer",
            "description": "How many seconds of transcript before and after a match to include in that match's contextText. Example: contextWindowSeconds=5 pulls the surrounding ~10 seconds of dialogue around each hit. Default is 5."
          },
          "maxMatchesPerVideo": {
            "title": "🚫 Max Matches Returned Per Video",
            "minimum": 0,
            "type": "integer",
            "description": "Caps how many individual match rows are returned in matches[] for a single video (earliest first). 0 = unlimited. This only trims the returned list - totalMatches, matchedKeywords and keywordDensityPer1000Words always reflect the true, uncapped count. Default is 0 (unlimited)."
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          "proxyConfiguration": {
            "title": "🛡️ Proxy Configuration",
            "type": "object",
            "description": "Configure proxy preferences for better reliability when needed. Leave default settings for normal use."
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YouTube Video Subtitles Scraper With Keyword Search OpenAPI definition

OpenAPI is a standard for designing and describing RESTful APIs, allowing developers to define API structure, endpoints, and data formats in a machine-readable way. It simplifies API development, integration, and documentation.

OpenAPI is effective when used with AI agents and GPTs by standardizing how these systems interact with various APIs, for reliable integrations and efficient communication.

By defining machine-readable API specifications, OpenAPI allows AI models like GPTs to understand and use varied data sources, improving accuracy. This accelerates development, reduces errors, and provides context-aware responses, making OpenAPI a core component for AI applications.

You can download the OpenAPI definitions for YouTube Video Subtitles Scraper With Keyword Search from the options below:

OpenAPI.json

If you’d like to learn more about how OpenAPI powers GPTs, read our blog post.

You can also check out our other API clients:

YouTube Video Subtitles Scraper With Keyword Search API in Python

YouTube Video Subtitles Scraper With Keyword Search API in JavaScript

YouTube Video Subtitles Scraper With Keyword Search API through CLI

YouTube Video Subtitles Scraper With Keyword Search API

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