Scavio for YouTube Transcript Knowledge Base

The Problem

Valuable knowledge is locked inside YouTube videos with no structured way to search across transcripts. Teams want to build internal knowledge bases from educational content, conference talks, and tutorial videos.

How Scavio Helps

• YouTube search discovers relevant videos by topic automatically
• MongoDB text indexes enable full-text search across all transcripts
• Weighted indexes prioritize title matches over incidental transcript mentions
• Daily pipeline discovers new videos and updates the knowledge base
• Cost: $0.25/day for 50 topic discovery queries

Relevant Platforms

Quick Start: Python Example

Here is a quick example searching YouTube for "A developer education team builds a searchable KB of coding tutorials. Scavio YouTube search finds relevant videos for 50 topics ($0.25/day). youtube-transcript-api extracts transcripts. MongoDB text index with 10x weight on title and 1x on transcript enables search. Team members search 'react server components' and find 12 matching tutorials ranked by relevance, with direct links to video timestamps.":

import requests

API_KEY = "your_scavio_api_key"

response = requests.post(
    "https://api.scavio.dev/api/v1/youtube/search",
    headers={
        "x-api-key": API_KEY,
        "Content-Type": "application/json",
    },
    json={"query": query},
)

data = response.json()
for video in data.get("videos", [])[:5]:
    print(f"{video['title']} — {video.get('views', 'N/A')} views")

Built for Knowledge management teams, developer education programs, content researchers, training departments

Scavio handles the search infrastructure — proxies, CAPTCHAs, rate limits, and anti-bot detection — so you can focus on building your youtube transcript knowledge base solution. The API returns structured JSON that is ready for processing, analysis, or feeding into AI agents.

Start with the free tier (250 credits/month, no credit card required) and scale to paid plans when you need higher volume.