Apple Podcasts Scraper

Apple Podcasts as rows, for any country: search shows by keyword, read the daily top charts, get full podcast details (publisher, genres, artwork, feed URL, episode count, latest release), the episodes with description, release date, duration and audio file URL (the latest 200 from Apple in one request, or the whole archive from the show's own feed with season and episode numbers), and the listener reviews with ratings from any storefront. A since-last-run checkpoint turns a daily schedule into a feed of new episodes. $1.80 per 1,000 podcasts, $0.60 per 1,000 episodes, $0.20 per 1,000 reviews. Summaries and errors are free. The first 25 results each month are free for every account.

Why this one

	This actor
Four sources, one run	Search, charts, details, episodes and reviews, through the feeds Apple publishes for them: the Search and Lookup API, the charts feed, each show's RSS feed and the reviews feed. No browser, no login, no key.
Episodes that pipelines can use	Every episode carries its audio URL, file type, duration in seconds, description, release date and Apple page. episodeSource: "rss" reads the show's own feed for the complete archive with season and episode numbers.
Any storefront	countries runs searches, charts and reviews once per storefront (us, gb, de, it, br…); reviews differ per country, which matters for international shows.
Monitoring	onlyNewSinceLastRun remembers the newest episode date per podcast and returns only newer episodes next time.
Honest numbers	Apple publishes no aggregate rating for podcasts, so the actor does not invent one; with reviews on, the free summary carries the average of the reviews it fetched, per podcast.
Price	$0.0018 per podcast, $0.0006 per episode, $0.0002 per review, Apify's default $0.00005 start fee. No platform usage charged on top.

What people use it for

• Transcription and summarisation pipelines: the audio URLs of this morning's new episodes, straight into Whisper or an LLM.
• Podcast PR and guest booking: shows by topic and country, with publisher, size, latest release and feed.
• Chart tracking: the top 200 in several countries every day, with positions, into a sheet.
• Listener sentiment: reviews and ratings of competing shows across storefronts.
• AI agents: "find podcasts about X and their latest episodes" as structured data through the Apify MCP server.

Example tasks

Ready-made configurations you can open, copy and run as they are:

• New episodes of the podcasts you follow, daily, with audio: two shows checked daily for new episodes with the checkpoint on.

Input

Field	Type	Default	Description
searchQueries	array	–	Podcast searches, one per line.
podcasts	array	[]	Apple IDs (1434243584) or Apple Podcasts URLs.
charts	array	[]	top, top-subscriber.
chartSize	integer	50	Entries per chart and country, up to 200.
countries	array	["us"]	Storefront codes.
maxPodcastsPerQuery	integer	20	Up to 200.
includeEpisodes	boolean	true	One episode row per episode.
episodeSource	string	apple	apple (latest 200, one request) or rss (whole archive, one request per show).
maxEpisodesPerPodcast	integer	50	Newest first.
episodesAfter	string	–	2026-01-01, 7d, 30d, 12w.
includeReviews	boolean	false	One review row per review, newest first, per country.
maxReviewsPerPodcast	integer	50	Up to 500 per country.
onlyNewSinceLastRun	boolean	false	Monitoring mode for episodes.
checkpointStoreName	string	apple-podcasts-state	Key-value store for the checkpoints.

At least one of searchQueries, podcasts or charts is required.

{
    "searchQueries": ["artificial intelligence"],
    "podcasts": ["1434243584", "https://podcasts.apple.com/us/podcast/the-daily/id1200361736"],
    "charts": ["top"],
    "chartSize": 50,
    "countries": ["us", "gb"],
    "includeEpisodes": true,
    "maxEpisodesPerPodcast": 10,
    "includeReviews": true,
    "maxReviewsPerPodcast": 50
}

Output

Five record types share one dataset, told apart by type: podcast, episode, review (charged), summary and error (free). Real rows, long fields shortened:

{
  "type": "podcast",
  "id": "1406537385",
  "name": "Practical AI",
  "publisher": "Practical AI LLC",
  "url": "https://podcasts.apple.com/us/podcast/practical-ai/id1406537385?uo=4",
  "feedUrl": "https://changelog.com/practicalai/feed",
  "artwork": "https://is1-ssl.mzstatic.com/image/thumb/Podcasts211/v4/…/600x600bb.jpg",
  "genres": ["Technology", "Podcasts"],
  "primaryGenre": "Technology",
  "episodeCount": 337,
  "latestReleaseDate": "2026-10-29T09:00:00.000Z",
  "explicit": false,
  "contentRating": "Clean",
  "country": "us",
  "query": "artificial intelligence",
  "chart": null,
  "chartPosition": null,
  "scrapedAt": "2026-11-02T14:05:12.000Z"
}

{
  "type": "episode",
  "podcastId": "1434243584",
  "podcastName": "Lex Fridman Podcast",
  "id": "1000798266396",
  "guid": "https://lexfridman.com/?p=7807",
  "title": "#503 – AI Crisis in Math: Navier-Stokes, Riemann Hypothesis & Complexity Theory",
  "description": "…",
  "releaseDate": "2026-10-26T22:52:28.000Z",
  "durationSeconds": 13360,
  "audioUrl": "https://media.blubrry.com/takeituneasy/ins.blubrry.com/takeituneasy/lex_ai_math_ai_crisis.mp3",
  "fileType": "mp3",
  "url": "https://podcasts.apple.com/us/podcast/…/id1434243584?i=1000798266396&uo=4",
  "seasonNumber": null,
  "episodeNumber": null,
  "episodeType": null,
  "explicit": false,
  "artwork": "https://is1-ssl.mzstatic.com/image/thumb/…/600x600bb.jpg",
  "source": "apple"
}

{
  "type": "review",
  "podcastId": "1406537385",
  "country": "us",
  "id": "14674368862",
  "rating": 1,
  "title": "Drunk on the Kool-Aid",
  "text": "This podcast was decent for a while, but it's really tailed off recently…",
  "author": "PHISHSIHd",
  "date": "2026-10-16T17:57:18.000Z",
  "voteSum": 0,
  "voteCount": 0,
  "url": "https://itunes.apple.com/us/review?id=1406537385&type=Podcast"
}

Field	Notes
podcast.episodeCount, latestReleaseDate	As Apple reports them for the show.
podcast.chart, chartPosition	Set when the podcast came from a chart.
episode.durationSeconds, audioUrl, fileType	From Apple or the feed's enclosure.
episode.seasonNumber, episodeNumber, episodeType	Only with episodeSource: "rss", when the feed states them.
episode.source	apple or rss.
review.rating	1 to 5. Reviews are per storefront; voteSum and voteCount are Apple's helpfulness votes.

summary (free, one per search, chart or podcast input): status (COMPLETE, PARTIAL, EMPTY, ERROR), podcastsFound, and per podcast the episodes and reviews delivered, the newest episode date, the average rating of the reviews fetched and a note when the feed failed and Apple's episodes were used instead.

error (free): {"type": "error", "target": "99999999999", "error": "Apple Podcasts has no podcast with ID 99999999999 in the us storefront."}

Pricing and cost examples

Try it free. The first 25 results each calendar month are free for every Apify account, with nothing to enter: the actor keeps count in a small key-value store in your account (free-slice-apple-podcasts-scraper) and charges only from the 26th on. The free results are real results you keep; the counter resets on the first of each month.

Job	Rows	Cost
Daily new episodes of 50 shows, about 1 a day each (checkpoint on)	50 podcasts + 50 episodes a day	$0.12 a day
Top 200 in 5 countries, podcasts only	1,000	$1.80
100 shows with their latest 100 episodes	100 + 10,000	$6.18
Reviews of 20 shows, 200 each, 3 storefronts	20 + 12,000 reviews	$2.44

Platform compute is included. A run that finds nothing new costs only Apify's $0.00005 start fee.

Discounts for paid Apify plans, applied automatically to the buyer's plan: Bronze 10% off, Silver 25% off, Gold and enterprise tiers 40% off the prices above. Free-plan users pay the listed price.

Monitoring: new episodes every morning

1. Create a task from this actor with your shows in podcasts, includeEpisodes: true, episodesAfter: "30d" for the first run and onlyNewSinceLastRun: true.
2. Add an Apify schedule (daily is plenty).
3. Add an integration on the task: Slack, e-mail, Google Sheets, Make, Zapier, n8n or a webhook. Each run delivers only new episodes with their audio URLs; the summary tells you per show what was found.

The checkpoint is the newest episode date per podcast, kept in the key-value store named in checkpointStoreName. To start over, change the name or delete the store.

Run it from your code

Node.js:

import { ApifyClient } from 'apify-client';
const client = new ApifyClient({ token: 'YOUR_APIFY_TOKEN' });
const run = await client.actor('agentsgearbox/apple-podcasts-scraper').call({
    searchQueries: ['artificial intelligence'], countries: ['us'], maxPodcastsPerQuery: 10, includeEpisodes: true, maxEpisodesPerPodcast: 5,
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items.filter((i) => i.type === 'episode').map((i) => [i.podcastName, i.title, i.durationSeconds, i.audioUrl]));

Python:

from apify_client import ApifyClient
client = ApifyClient("YOUR_APIFY_TOKEN")
run = client.actor("agentsgearbox/apple-podcasts-scraper").call(run_input={
    "charts": ["top"], "chartSize": 100, "countries": ["us", "gb", "de"], "includeEpisodes": False})
podcasts = [i for i in client.dataset(run["defaultDatasetId"]).iterate_items() if i["type"] == "podcast"]

cURL (synchronous, returns the dataset):

curl -X POST "https://api.apify.com/v2/acts/agentsgearbox~apple-podcasts-scraper/run-sync-get-dataset-items?token=YOUR_APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"podcasts": ["1434243584"], "includeEpisodes": true, "maxEpisodesPerPodcast": 10}'

For AI agents

Give your agent hands. Apple Podcasts pages are rendered applications; this actor returns the same data as JSON, priced per row and known in advance. "Find podcasts about longevity and give me the audio of their latest episode" becomes one tool call.

• MCP, this actor only: add https://mcp.apify.com?tools=agentsgearbox/apple-podcasts-scraper to Claude Desktop, Claude Code, Cursor or any MCP client (with your Apify token), then ask for "the ten most popular podcasts about personal finance in the UK with their latest episode".

• MCP, all agentsgearbox actors: https://mcp.apify.com?tools=agentsgearbox/telegram-channel-scraper,agentsgearbox/google-play-reviews-scraper,agentsgearbox/substack-scraper,agentsgearbox/google-news-scraper,agentsgearbox/brand-name-generator,agentsgearbox/ai-readiness-audit,agentsgearbox/company-lookup,agentsgearbox/app-intelligence,agentsgearbox/app-store-reviews-scraper,agentsgearbox/company-jobs-scraper,agentsgearbox/apple-podcasts-scraper,agentsgearbox/remote-jobs-scraper

• No Apify account? This actor is eligible for Apify's agentic payments: an agent can buy a spend-capped token through agi.apify.com (x402, MPP or Skyfire) and call the API directly.
• Prices are per row and known in advance, so the agent can set a spending limit; an unknown ID comes back as a free error record, not as a failed run.

Limitations, stated plainly

• Apple's lookup returns at most 200 episodes per show; for older episodes use episodeSource: "rss", which reads the show's own feed (a few feeds are huge or protected, in which case the actor falls back to Apple's 200 and says so in the summary).
• Apple publishes no aggregate rating or review count for podcasts; the average in the summary is computed from the reviews fetched.
• Apple's reviews feed holds at most 500 reviews per show and storefront, newest first, and serves no reviews at all for some shows.
• Apple's Search API allows about 20 requests a minute per IP; the actor paces itself, so a run over hundreds of shows takes minutes rather than seconds.
• Transcripts are not published by Apple; the audio URL is what you feed to a transcription model.

Troubleshooting

Symptom	Cause and fix
error: no podcast with ID …	Wrong ID or URL. The ID is the number after id in the show's Apple Podcasts URL.
0 episodes with the checkpoint on	Nothing new since the last run.
Episodes stop at 200	Apple's limit; switch episodeSource to rss.
summary.note says the feed failed	The show's feed timed out or is not public; Apple's latest 200 were used.
status: "PARTIAL"	Your spending limit for the run was reached. Raise it or lower the limits.

Track record

• Published 2 November 2026 and tested every day since by an automated run on the Apify platform. The Store's run statistics on this page reflect those runs with a delay of up to a day.
• No browser, so a run cannot fail on Chrome crashes or memory limits.
• Every actor from this account is monitored daily, so a change on Apple's side is normally fixed the same day.

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All of them are pay-per-event, run without a browser, and are compared with their alternatives on agentsgearbox.com.

Support

Open an issue on this actor's Issues tab, usually answered within a day, or email support@agentsgearbox.com. More actors and daily comparisons of scrapers for 200+ websites at agentsgearbox.com.

Legal and fair use

This actor is an independent tool, not affiliated with or endorsed by Apple; Apple Podcasts is a trademark of Apple Inc., used only to name the service the actor reads. It uses Apple's public Search and Lookup API and feeds, each show's own RSS feed, which exists to be read by any client, and Apple's public reviews feed, without keys or logins, and it stores nothing on your behalf beyond your own Apify datasets. Episode audio and artwork belong to their publishers: link to them, play them in your own tools, analyse them, but do not re-host them as your own. Reviews are written by listeners; quote them with attribution.