Podcast Data in n8n, No Code Required

July 29, 2026

You want to pull podcast episodes, transcripts, or chapter data into an n8n workflow — feeding a newsletter, a Slack digest, a content pipeline, whatever. The problem: most podcast APIs assume you’re a developer wiring up authentication, pagination, and response parsing by hand. n8n doesn’t need any of that ceremony, and neither does PodKit.

This is a five-minute setup using n8n’s built-in HTTP Request node — no custom package, no code node required.

Step 1: Get a free PodKit key

Grab one at podkitapp.com — 500 requests a month, no card needed. You’ll use it in one header.

Step 2: Add an HTTP Request node

Drop an HTTP Request node into your workflow and configure it:

  • Method: GET
  • URL: https://podkitapp.com/v1/search?q=technology
  • Headers: x-api-key: pk_your_key

Run it once. You’ll get back clean JSON — no XML to parse, no RSS quirks to handle:

{
  "query": "technology",
  "source": "itunes",
  "results": [
    {
      "id": 1200361736,
      "title": "The Daily Tech",
      "feedUrl": "https://feeds.example.com/tech.xml"
    }
  ]
}

Step 3: Chain it to episodes, chapters, or transcripts

Every result’s id is what feeds the next call. Add a second HTTP Request node downstream, pointed at:

https://podkitapp.com/v1/podcast/{{ $json.results[0].id }}

…and n8n will resolve that expression against the previous node’s output automatically. From there, each episode carries its own id — chain it into /v1/episode/{id}/chapters or /v1/episode/{id}/transcript the same way, and you’ve got a full search → episode → transcript pipeline with zero custom code.

Why this works well in n8n specifically

  • Transcripts count as normal requests — not a separate metered add-on, so a transcript-heavy workflow doesn’t quietly rack up a different bill than your search calls.
  • Client-side caching is allowed — if your workflow polls on a schedule, you can cache upstream in n8n (or just let PodKit’s own 24-hour cache absorb repeat lookups) without violating any terms.
  • One key, one quota — search, metadata, chapters, and transcripts all draw from the same plan, so you’re not juggling separate API keys per endpoint.

Where to go from here

If your workflow needs an AI step — summarizing an episode, extracting quotes — PodKit also ships an MCP server, so an agent step in your pipeline can call the same data as tools instead of raw HTTP, if that fits your setup better.

Full endpoint reference: podkitapp.com/docs.

See the Search API →   Read the docs

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