Use Case

Build a YouTube Video Search Engine

The Problem

YouTube's search only works on titles, descriptions, and tags. You cannot search for specific words or phrases spoken within videos. Researchers, content curators, and developers need the ability to search inside video content to find exactly what they are looking for.

The Solution

YouTubeTranscripts.co extracts searchable text from any video. Index transcripts in Elasticsearch, Typesense, or a vector database for full-text and semantic search. Build applications that let users search for specific topics, quotes, or discussions within video libraries.

Implementation Example

import httpx

API_KEY = "YOUR_API_KEY"

# Fetch and index a transcript
resp = httpx.get(
    "https://api.youtubetranscripts.co/v1/transcript",
    params={"url": "https://youtube.com/watch?v=VIDEO_ID"},
    headers={"x-api-key": API_KEY},
)
data = resp.json()

# Simple keyword search across transcript segments
def search_transcript(transcript: list, query: str) -> list:
    results = []
    query_lower = query.lower()
    for segment in transcript:
        if query_lower in segment["text"].lower():
            results.append({
                "text": segment["text"],
                "timestamp": segment["start"],
                "url": f"https://youtube.com/watch?v=VIDEO_ID&t={int(segment['start'])}",
            })
    return results

matches = search_transcript(data["transcript"], "machine learning")
for match in matches:
    print(f"[{match['timestamp']:.0f}s] {match['text']}")
    print(f"  Link: {match['url']}")

Why Developers Choose YouTubeTranscripts.co

Search for specific words spoken in any video

Link results directly to video timestamps

Index thousands of videos for full-text search

Combine with vector embeddings for semantic search

Build internal knowledge bases from video content

Power search features for video platforms and tools

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