BulkTranscripts logo BulkTranscripts

Workflow · Teams

Whole channel → knowledge base

The answer exists — in minute 34 of a video nobody will rewatch. As text, the same archive is searchable in seconds and quotable with links.

Runs on the MCP server (one sign-in, 30 free credits) or the REST API · repeat reads from your library are free.

How it works

  1. List the channel's videos (up to 1,000) with get_channel_videos.
  2. Batch-fetch transcripts — or run the whole channel through the bulk workspace in one job.
  3. Load the combined export into Notion, NotebookLM, or your internal search.
  4. New uploads get appended via the free latest-uploads check, so the base stays current.

One job, not one hundred

For archives this size the bulk workspace is usually the faster path: paste the channel URL, get every available transcript as individual files or one combined, AI-ready document with per-video headers. The API path below does the same thing scriptably.

Or script it against the REST API:

# the whole archive, scripted
curl "https://bulktranscripts.co/api/v1/channel/videos?channel=@yourchannel&limit=1000" \
  | jq -r '.videos[].id' \
  | while read id; do curl "https://bulktranscripts.co/api/v1/transcript?video=$id&format=md" \
      -o "kb/$id.md"; done

Agent prompt — paste into Claude, ChatGPT, or any assistant connected to the BulkTranscripts MCP server:

List every video on @yourchannel about [PRODUCT AREA], fetch those
transcripts, and organize them into a knowledge base outline: group by
topic, note which video covers what, and flag topics covered by no video.

What you’ll need

An MCP-capable assistant (Claude, ChatGPT, Cursor) connected to https://bulktranscripts.co/mcp — one sign-in includes 30 free credits — or a license key for the REST API. Transcripts already in your library are re-read free, so iterating on the same videos costs nothing after the first pass.

Common questions

What does a 200-video channel cost?

About 200 credits on first ingestion (one per new transcript) — the $4.99 starter pack covers it. Keeping it current afterwards costs only what is newly published.

Which export should I feed to AI tools?

The combined AI-ready export — one file, every transcript, per-video headers with titles and links — was designed for NotebookLM, Claude Projects, and custom GPTs.

More workflows

Updated