Scavio for YouTube Research Notes for Obsidian

The Problem

Researchers who use Obsidian for knowledge management manually search YouTube, copy video metadata, and create notes by hand. This process is slow and doesn't scale for broad topic research.

How Scavio Helps

• Automated YouTube search and note creation
• Structured YAML frontmatter for Dataview queries
• Interlinked notes build a research graph automatically
• Consistent note format across all video entries
• Batch processing handles 10-20 videos per topic search

Relevant Platforms

Quick Start: Python Example

Here is a quick example searching YouTube for "Researcher studying 'LLM grounding techniques' triggers the workflow. YouTube search returns 15 relevant videos. Script creates 15 Obsidian notes with title, channel, views, link, and description. Index note links to all 15. Dataview query shows all videos sorted by view count.":

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 Researchers, students, knowledge workers using Obsidian, PKM enthusiasts

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

Start with the free tier (50 credits on signup, no credit card required) and scale to paid plans when you need higher volume.