Apple Podcasts Scraper - Search, Lookup & Episodes

Search Apple Podcasts by keyword or podcast ID through the official iTunes Search and Lookup APIs, get RSS feed URLs, genres, episode counts and last release date, and optionally the latest episodes with audio URLs. Plain HTTP, no login.

What does this Actor do?

Apple Podcasts is the largest podcast directory, and every listing points to a public RSS feed. This Actor uses Apple's official iTunes Search API and Lookup API to find podcasts by keyword or ID and returns clean metadata - feed URL, author, genres, episode count, last release date, artwork and explicit flag. Optionally it reads each podcast's RSS feed and outputs the latest episodes with audio URLs, durations and descriptions.

Key features:

• Plain HTTP against official public endpoints - no browser, no proxy, no login, runs on 128 MB memory.
• Pay only for results: one charge per row saved; your maximum charge per run is always respected.
• maxItems hard cap (default 100) and bounded pagination - runs can never loop forever.
• Incremental mode via a since-date so scheduled runs only fetch new data.
• Polite rate limiting, retries with exponential backoff and Retry-After support.
• Clean, flat, consistently named JSON fields ready for Excel, Google Sheets, BigQuery or your API.

Who is it for?

• Podcast guest booking & PR - build lists of active shows in a niche (filter by last release date) and reach hosts through their feed.
• Sponsorship and ad sales - find shows by topic and size them by episode count and frequency.
• Podcast analytics tools - seed your database with feed URLs and Apple IDs.
• Content research - monitor what competitors and thought leaders publish each week.
• Lead generation - podcasters are businesses; their feeds often include owner emails and websites.

How it works

Search terms go to itunes.apple.com/search (up to 200 results per term) and IDs go to itunes.apple.com/lookup in batches of 50. Apple allows roughly 20 requests per minute, so the Actor spaces iTunes calls by about 3 seconds by default and retries politely. RSS feeds are fetched directly from the podcast host with a light regex parser - no browser - and failures on a single feed never stop the run.

Input

Field	Type	Default	Description
searchTerms	array	-	Keywords to search podcasts for (e.g. 'saas marketing').
podcastIds	array	[]	e.g. 1200361736 or https://podcasts.apple.com/us/podcast/the-daily/id1200361736
country	string	"us"	Two-letter iTunes storefront code.
maxItems	integer	100	Hard cap on podcasts saved and charged.
maxPodcastsPerSearch	integer	20	iTunes returns at most 200 per query.
expandSearch	boolean	true	If a multi-word phrase has fewer iTunes matches than requested, its individual words are also searched to fill the quota. Set false for exact-phrase results only.
includeEpisodes	boolean	false	Fetch each podcast's RSS feed and output episodes (charged as 'episode').
maxEpisodesPerPodcast	integer	10	Max episodes per podcast
sinceDate	string	-	ISO date. Skips podcasts whose last release is older, and episodes published before it.
delayMs	integer	3200	Apple allows ~20 requests/minute; keep >= 3000.

Example input

{
  "searchTerms": [
    "saas marketing",
    "indie hackers"
  ],
  "country": "us",
  "maxItems": 100,
  "includeEpisodes": true,
  "maxEpisodesPerPodcast": 5,
  "sinceDate": "2026-09-01"
}

Output

Each result is one row in the default dataset. You can download it as JSON, CSV, Excel, XML or HTML, or read it through the Apify API. A real row from a test run on 26 October 2026:

{
  "type": "podcast",
  "podcastId": 1200361736,
  "name": "The Daily",
  "author": "The New York Times",
  "feedUrl": "https://feeds.simplecast.com/Sl5CSM3S",
  "appleUrl": "https://podcasts.apple.com/us/podcast/the-daily/id1200361736",
  "artworkUrl": "https://is1-ssl.mzstatic.com/image/thumb/Podcasts221/v4/ab/64/66/ab6466a9-9a7d-e20e-7a3d-bc5be37d29ce/mza_15084852813176276273.jpg/600x600bb.jpg",
  "genres": [
    "Daily News",
    "Podcasts",
    "News"
  ],
  "primaryGenre": "Daily News",
  "episodeCount": 2760,
  "lastReleaseDate": "2026-10-25T10:00:00Z",
  "country": "USA",
  "explicit": false,
  "contentAdvisoryRating": "Clean",
  "source": "lookup"
}

Tips

• Set sinceDate to keep only podcasts that released something recently - a quick filter for active shows.
• Use several narrow search terms rather than one broad one; Apple caps each query at 200 results.
• Change country to search other storefronts (gb, de, jp...).
• Episodes are charged separately so you only pay for them when you turn them on.

Pricing

This Actor uses pay-per-event pricing: about $1.00 per 1,000 podcasts and $0.30 per 1,000 episodes. There is no monthly rental fee. Platform usage is minimal because the Actor runs on 128 MB with plain HTTP requests. Set Maximum cost per run in the run options and the Actor stops cleanly as soon as the limit is reached - you are never charged beyond it.

Scheduling and integrations

Create an Apify Schedule (for example daily at 08:00) and pass a since-date to get only new items each time. Connect the dataset to Google Sheets, Slack, Zapier, Make, n8n or a webhook to receive results automatically, or call the Actor from Python or JavaScript using the Apify API client.

Limitations

The iTunes Search API does not expose ratings, review counts or chart positions. Some podcasts hide or move their RSS feed; those still return metadata but no episodes.

FAQ

Do I need an account or API key on the source site? No. Only public, unauthenticated endpoints are used.

Do I need proxies? No. The Actor makes a small number of well-spaced requests to official APIs, so datacenter IPs work fine.

Why did my run return fewer items than maxItems? The source simply had no more items matching your filters and date range, or your maximum cost per run was reached.

Is this legal? The Actor only reads publicly available data through documented public endpoints. You are responsible for using the data in line with the source's terms and applicable laws such as GDPR, especially for personal data.

Something broke? Open an issue on the Actor's Issues tab with your run ID and we will fix it quickly.