Transcribe Podcast RSS Episodes with n8n & Apify

Turn New Podcast Episodes into Ready-to-Use Transcripts—Automatically

This n8n workflow watches your podcast RSS feed for newly published episodes, extracts the audio URL, and uses the Apify Audio Transcriber Actor to generate transcripts—then outputs only the completed results for your next step.

What this workflow does

• Polls an RSS feed on a schedule and reads newly published items.
• Extracts episode audio URLs from the RSS enclosure, with a fallback to the item link, along with basic metadata like title and publish date.
• Runs transcription with Apify by sending the audio URL to the kaz_kakyo/audio-transcriber Actor.
• Filters results to keep only dataset rows where type is transcript, excluding error/skip rows.
• Outputs one item per transcript to the final destination step you replace or connect.

Use cases

• Build searchable episode archives by automatically transcribing every new podcast release.
• Power content workflows where transcripts are needed for summaries, SEO pages, or knowledge base updates (using your preferred downstream destination).
• Operational automation for SaaS teams who want consistent, scheduled ingestion from RSS plus transcription via Apify.

Technical details

• RSS Feed Read Trigger for polling and detecting new podcast episodes.
• Code node(s) to extract the audio URL (from enclosure with link fallback) and pass metadata.
• @apify/n8n-nodes-apify (Apify community node) to run kaz_kakyo/audio-transcriber.
• No Op and Sticky Note nodes for structure/clarity.
• Dataset filtering to keep only successful transcript rows and output them one-by-one.

Setup at a glance

Install and enable the @apify/n8n-nodes-apify community node, add your Apify API token credential, set your podcast RSS feed URL, choose a polling interval, and optionally adjust Apify run settings (e.g., “Maximum Cost per Run (USD)”) and Actor input JSON.