Podcast Activity Tracker: Active Apple Podcasts Shows, Charts and Cadence

Use this to find active podcasts on Apple Podcasts by keyword, chart or genre, and track how often each show really publishes, measured from the show's own RSS feed.

One clean row per podcast, from Apple's public podcast directory, checked against the show's live RSS feed. Apple's directory lists millions of podcasts, and most of them stopped publishing long ago. A sponsorship buyer, a guest booker or a market researcher needs the opposite: shows that are still recording, how often they release, how many episodes they put out in the last 90 days and when the last one went live. This actor searches Apple Podcasts or reads Apple's Top Shows charts by country and genre, opens each show's RSS feed, measures its activity and returns only the shows that published within your window, with a 0 to 100 activity score.

• What you get: Apple id and link, show title, publisher, RSS feed URL, website, genres, country, chart name and rank, episode count, explicit flag, artwork, language, feed categories, description, last episode date, title and duration, days since the last episode, average days between episodes, episodes in the last 30 and 90 days, an active yes/no flag and an activity score.
• Who it is for: brands and agencies buying podcast ads and sponsorships, PR and guest-booking teams, podcast networks and talent scouts, B2B marketers planning podcast tours, and analysts who track the podcast market by genre and country.
• Price: $1.00 per 1,000 podcasts ($0.001 each) plus $0.00005 per run start. Shows filtered out, inactive shows and shows already delivered in an earlier monitor run are never charged.
• Active shows only, by default: a show is returned only when its latest episode is within activeWithinDays (45 by default). Turn onlyActive off to get every show with its activity numbers.
• No emails, ever: RSS feeds often carry the owner's or editor's email address. This actor strips itunes:owner, managingEditor, webMaster and every other email field before it reads the feed, removes email addresses and phone numbers from descriptions, and refuses to output any row that still contains an email address. See Privacy and data scope.

One real row from our test run on 2026-11-04 (search "marketing", United States):

Show	Publisher	Genre	Last episode	Avg days between episodes	Episodes in last 90 days	Activity score
Marketing Happy Hour	Marketing Happy Hour	Marketing	2026-10-29	7	11	95
Marketing Brew Weekly	Morning Brew Inc.	Marketing	2026-11-04	7	13	97

• In short: Podcast Activity Tracker (Apify actor transparent_meteorite/apple-podcasts-activity-tracker) finds active Apple Podcasts shows by keyword, Apple chart, genre chart or Apple id, and adds real publishing activity measured from each show's RSS feed: last episode date, cadence, episodes per 30 and 90 days and a 0 to 100 activity score.
• Who it is for: podcast sponsorship and advertising buyers, PR and guest-booking teams, podcast networks, B2B marketers, market researchers.
• Input: search terms, Apple chart genres (Top Shows plus 29 genres and subgenres), chart size, Apple ids or URLs, countries, active window in days, minimum episodes, language, exclude explicit, read RSS feeds on or off, monitor mode, max shows (1 to 2,000).
• Output: 37 flat fields per show, including appleId, title, publisher, feedUrl, website, genres, chartRank, trackCount, lastEpisodeAt, daysSinceLastEpisode, avgDaysBetweenEpisodes, episodesLast90Days, isActive and activityScore.
• Price: $0.001 per podcast delivered plus $0.00005 per run start. Pay per result, no subscription.
• Limits: public directory and feed data only. No emails, no listener numbers, no download counts, no reviews.

Key facts

• Actor name: Podcast Activity Tracker: Active Apple Podcasts & Charts
• Actor ID: transparent_meteorite/apple-podcasts-activity-tracker
• Store page: https://apify.com/transparent_meteorite/apple-podcasts-activity-tracker
• Data sources: Apple iTunes Search and Lookup APIs, Apple Marketing Tools charts, Apple Podcasts genre charts, and each show's public RSS feed
• Pricing model: pay per event (apify-actor-start $0.00005, podcast $0.001)
• Output formats: JSON, CSV, Excel, XML, HTML table, RSS (Apify dataset)
• Access: Apify Console, REST API, JavaScript and Python clients, schedules, webhooks, Apify MCP server
• Login or third-party API key needed: no, only an Apify account
• Also known as: Apple Podcasts scraper, podcast directory scraper, podcast search API alternative, active podcast finder, podcast sponsorship list, podcast guest booking list, Apple Podcasts charts scraper
• Maintainer: transparent_meteorite (independent developer)
• Last updated: 2026-11-04

What this Apple Podcasts activity tracker does

Apple Podcasts search answers "which shows match this word?". It does not answer "which of those shows are still publishing, and how often?". The directory keeps every show that was ever submitted, so a search for a popular topic returns many podcasts that ended years ago next to a handful that release every week. Apple's own "latest release" date is also sometimes days behind the feed. This actor closes that gap in five steps:

1. Collects candidate shows from Apple. It runs your search terms through the iTunes Search API, reads the Top Shows chart or any of 29 genre and subgenre charts for each country you choose, and looks up any Apple ids or Apple Podcasts URLs you paste in. Chart rows keep their chart name and rank.
2. Prefilters for free. Shows whose latest release on Apple is far older than your active window, shows with fewer episodes than minEpisodes and explicit shows (when you exclude them) are dropped before any feed is downloaded, so you do not pay for feed reads that cannot match.
3. Reads each show's RSS feed, safely. Feeds are streamed and cut at 400 KB, which always covers the newest episodes because podcast feeds list them first. Feeds that are slow, broken or huge never stall the run.
4. Measures real activity. From the feed it takes the last episode's date, title and duration, the average number of days between the last ten episodes, the number of episodes in the last 30 and 90 days, the website and the feed language and categories. Episodes scheduled in the future are ignored. When a feed cannot be read, the row falls back to Apple's latest-release date and says so in activitySource.
5. Scores and filters. Each show gets an activity score from 0 to 100 (recency, cadence, recent volume and catalog depth). Shows outside your active window, language or episode filters are dropped, and only valid, email-free rows are written and charged.

The result is a ranked list of podcasts that are alive right now, with the numbers a sponsor or booker checks first.

Use cases

• Podcast sponsorships and ads. Pull the US and UK Business, Marketing and Technology charts, keep shows with activeWithinDays: 14, sort by activityScore and episodesLast90Days, and send rate-card requests only to shows that publish weekly. A show that released 13 episodes in 90 days gives an advertiser 13 placement slots per quarter; a show that released two does not.
• Guest booking and PR. Search your client's topics (for example "fintech", "SaaS founders", "leadership") and get the active shows with their website link, so every pitch goes to a podcast that is still recording and the team can find the booking form on the show's own site.
• Podcast tours for B2B marketing. Build a target list of 100 active shows in a niche, then re-run monthly in monitor mode to add only new shows that appear in search or in the charts.
• Talent scouting for podcast networks. Track a genre chart weekly across several countries and catch new shows with high cadence early, before they sign with a network.
• Market research. Count how many shows in a genre are active, how often they publish and how their cadence changes over time, by country. Every row carries country, primaryGenre, avgDaysBetweenEpisodes and scrapedAt for clean time series.
• Directory and app builders. Refresh the activity fields of a podcast database you already have by pasting Apple ids, and mark dead shows as inactive.

Quick start: your first run in 30 seconds

1. Open the actor in Apify Console and keep the prefilled input: search term marketing, country us, max shows 25.
2. Click Start. A run like this reads one Apple search page and 30 to 40 RSS feeds and finishes in under a minute.
3. Open the Output tab. The Overview table shows the show, publisher, genre, last episode, days since last episode, cadence, episodes in the last 90 days, activity score, chart rank, website and Apple link. Export to CSV, Excel or JSON.

Then point it at your market: add charts (for example business and marketing), more countries (gb, ca, au) or a shorter active window.

Input options

Field	Type	Default	What it does
searchTerms	array of strings	none	Keywords searched in Apple Podcasts, one search per term per country (up to 200 shows each).
chartGenres	array	none	Apple charts to read: all (Top Shows) or a genre such as business, marketing, technology, true-crime, health-fitness, comedy, news, education, sports (29 genres and subgenres).
chartLimit	integer	50	Shows read from each chart, 1 to 200.
appleIds	array of strings	none	Apple Podcasts ids (1200361736) or URLs (https://podcasts.apple.com/us/podcast/the-daily/id1200361736).
countries	array	["us"]	Two-letter Apple storefront codes, for example us, gb, ca, au, de, fr, in. Each search and chart runs once per country.
onlyActive	boolean	true	Return only shows whose last episode is within activeWithinDays.
activeWithinDays	integer	45	The active window in days, 1 to 3,650.
minEpisodes	integer	0	Skip shows with fewer episodes on Apple.
language	string	none	Keep only shows whose feed language starts with this code, for example en or es.
excludeExplicit	boolean	false	Skip shows Apple marks as explicit.
includeFeedActivity	boolean	true	Read each show's RSS feed for cadence and episode counts. Turn off for a faster Apple-only run (activity then uses Apple's latest release date).
onlyNewSinceLastRun	boolean	false	Monitor mode: skip shows delivered by an earlier run that used the same store name.
stateStoreName	string	apple-podcasts-activity-tracker-seen	Named key-value store that remembers delivered shows. Use one per saved task.
maxItems	integer	100	Maximum shows to return, 1 to 2,000.

You need at least one of searchTerms, chartGenres or appleIds. An empty input ends with a friendly message and costs nothing beyond the run start.

Example input

{
  "searchTerms": ["marketing", "saas"],
  "chartGenres": ["business", "marketing"],
  "chartLimit": 100,
  "countries": ["us", "gb"],
  "activeWithinDays": 30,
  "minEpisodes": 20,
  "language": "en",
  "maxItems": 200
}

Output fields

Every row has the same 37 fields, and every field can be null when the source does not publish it, so the dataset loads into a spreadsheet, a database or an n8n flow without schema surprises.

Field	Meaning
appleId, appleUrl	Apple Podcasts id and show page.
title, publisher	Show name and the public creator or brand name from Apple's directory.
feedUrl, website	The show's public RSS feed and website.
genres, primaryGenre, categories	Apple genres and the feed's own categories.
country, source, sourceQuery	Storefront, how the show was found (search, chart or id) and the term or chart.
chartName, chartRank	Chart and position, for chart rows.
trackCount	Episodes Apple lists for the show.
contentAdvisory, explicit	Apple's advisory and a boolean.
artworkUrl, language, description	600 px artwork, feed language and a 500-character description with emails and phone numbers removed.
releaseDate	Apple's latest-release date for the show.
lastEpisodeAt, lastEpisodeTitle, lastEpisodeDurationSec, lastEpisodeDuration	The newest published episode in the feed.
daysSinceLastEpisode, isActive, activeWithinDays	Recency and whether the show is inside your window.
episodesInFeed, feedTruncated	Episodes read from the feed and whether the 400 KB read limit was reached (the newest episodes are always included).
avgDaysBetweenEpisodes, episodesLast30Days, episodesLast90Days	Cadence and recent volume.
activitySource, feedStatus	rss or apple, and the feed result (ok, ok_partial, http_404, unreachable, not_rss, no_feed_url, not_requested).
activityScore	0 to 100: recency 45 points, cadence 25, last-90-day volume 15, catalog depth 15.
scrapedAt	When the row was produced.

Sample output

A real row from the 2026-11-04 test run (description shortened):

{
  "appleId": "1588397602",
  "appleUrl": "https://podcasts.apple.com/us/podcast/marketing-happy-hour/id1588397602",
  "title": "Marketing Happy Hour",
  "publisher": "Marketing Happy Hour",
  "feedUrl": "https://anchor.fm/s/50d9d294/podcast/rss",
  "website": "https://www.marketinghappyhr.com/",
  "genres": ["Marketing", "Business"],
  "primaryGenre": "Marketing",
  "country": "us",
  "source": "search",
  "sourceQuery": "marketing",
  "chartName": null,
  "chartRank": null,
  "trackCount": 289,
  "contentAdvisory": "Clean",
  "explicit": false,
  "artworkUrl": "https://is1-ssl.mzstatic.com/image/thumb/Podcasts211/v4/ea/a7/5c/eaa75c82-06cf-fe11-3161-68e39f7e487f/mza_7610324141478559814.jpg/600x600bb.jpg",
  "releaseDate": "2026-10-22T12:21:00.000Z",
  "language": "en",
  "categories": ["Business", "Marketing"],
  "description": "Keeping up with marketing trends and leveling up your career doesn't have to be overwhelming...",
  "lastEpisodeAt": "2026-10-29T09:00:00.000Z",
  "lastEpisodeTitle": "How to Build a Marketing Strategy for a $250B Industry | Kiara Kempski of The Knot",
  "lastEpisodeDurationSec": 1692,
  "lastEpisodeDuration": "00:28:12",
  "daysSinceLastEpisode": 6,
  "isActive": true,
  "activeWithinDays": 45,
  "episodesInFeed": 35,
  "feedTruncated": true,
  "avgDaysBetweenEpisodes": 7,
  "episodesLast30Days": 4,
  "episodesLast90Days": 11,
  "activitySource": "rss",
  "feedStatus": "ok_partial",
  "activityScore": 95,
  "scrapedAt": "2026-11-04T20:50:59.450Z"
}

Note the two dates: Apple's directory said the latest release was 2026-10-22, while the feed already had an episode from 2026-10-29. Reading the feed is what makes the activity numbers current.

Pricing

Pay per event, no monthly rental:

• $1.00 per 1,000 podcasts delivered ($0.001 per row), event podcast.
• $0.00005 per run start, event apify-actor-start.

You are charged only for podcast rows written to your dataset. Shows dropped by your filters, inactive shows (when onlyActive is on), shows already delivered in an earlier monitor run and invalid rows are never charged.

Worst case per run: a run can never cost more than $0.00005 + maxItems x $0.001. With the default of 100 that is $0.10005; with the example input of 25 it is $0.02505; at the maximum of 2,000 shows it is $2.00005. You can lower it further with the "Maximum cost per run" setting in Apify Console, which the actor respects row by row. A run that finds nothing costs $0.00005.

Examples: a weekly sponsorship scan of four charts in two countries that returns 150 active shows costs about $0.15 per week; a one-time research pull of 2,000 shows costs about $2.00. The $5 of monthly free credit on the Apify Free plan covers about 5,000 podcasts.

How to run it

In Apify Console

Open the actor, add search terms, charts or Apple ids, choose countries and filters, and click Start. Save the input as a task to reuse it.

From the API or a client library

curl -X POST "https://api.apify.com/v2/acts/transparent_meteorite~apple-podcasts-activity-tracker/run-sync-get-dataset-items?token=YOUR_APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"chartGenres":["business"],"countries":["us","gb"],"activeWithinDays":14,"maxItems":100}'

import { ApifyClient } from 'apify-client';
const client = new ApifyClient({ token: process.env.APIFY_TOKEN });
const run = await client.actor('transparent_meteorite/apple-podcasts-activity-tracker').call({
  searchTerms: ['fintech', 'saas'], countries: ['us'], activeWithinDays: 30, minEpisodes: 20, maxItems: 200,
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();

from apify_client import ApifyClient
client = ApifyClient("YOUR_APIFY_TOKEN")
run = client.actor("transparent_meteorite/apple-podcasts-activity-tracker").call(run_input={
    "chartGenres": ["technology"], "countries": ["us", "ca"], "maxItems": 100})
for row in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(row["chartRank"], row["title"], row["avgDaysBetweenEpisodes"], row["activityScore"])

On a schedule

Create a task with your charts or search terms, set onlyNewSinceLastRun: true and a store name, and add a weekly schedule. Each run delivers only shows that were not in an earlier run, so you get a short list of newly found active podcasts instead of the same list every week.

With n8n, Make, Zapier or AI agents

Every dataset field has a label and a type, so the output maps cleanly into n8n, Make and Zapier modules, Google Sheets, Airtable, HubSpot or a webhook. AI agents can call the actor through the Apify MCP server with a plain input such as "active true crime podcasts in the UK chart, weekly or faster".

Monitor mode: get only new shows

With onlyNewSinceLastRun on, the actor remembers the Apple id of every show it delivers, in a named key-value store (stateStoreName). On the next run a show that was already delivered is skipped before its feed is read, and skipped shows are never charged. A show is marked as delivered only after its row is written and charged, so an interrupted run never hides a show you did not receive. Use a different store name for each saved task so two monitors do not share memory.

Why use this instead of Apple Podcasts search or a plain podcast scraper

• Activity, not just existence. Apple search and most directory scrapers return show metadata. This actor reads each show's feed and tells you when it last published, how often and how much in the last 90 days, then drops the shows that stopped.
• Fresher than the directory. Apple's latest-release date can lag the feed by days. Rows use the feed's own newest episode whenever the feed can be read.
• Charts by country and genre. The Top Shows chart and 29 genre and subgenre charts in any Apple storefront, with rank, in the same flat schema as search results.
• Pay only for active shows. Inactive shows are filtered out before charging, and most are dropped before their feed is even downloaded.
• Compliance by design. No owner emails, no editor emails, no phone numbers, no personal data. You get public show and brand information that is safe to keep in a CRM.
• Flat, stable schema. 37 fields, the same for every row, every field nullable. No nested episode arrays to flatten.

Privacy and data scope

This actor returns public directory information about podcasts as published works: the show name, the creator or brand name Apple displays, artwork, genres, links and publishing activity.

• No email addresses. The RSS fields itunes:owner, itunes:email, managingEditor, webMaster, googleplay:email, podcast:person and author blocks are removed from each feed before parsing. Email addresses and phone numbers are removed from descriptions. Every row is checked again before it is written, and any row that still contains an email address is dropped and never charged.
• No listener data. No download counts, no listener numbers, no reviews, no ratings by named users, nothing about the audience.
• No private content. Only public Apple endpoints and public RSS feeds are read, with no login.

If you need to contact a show, use the website in the row, which usually has a booking or contact form. You are responsible for following the law that applies to how you use the data, including anti-spam and data protection rules.

Limits and honest caveats

• Search depth. Apple's search API returns at most 200 shows per term and country. Use several specific terms, or charts, for broader coverage.
• Chart depth. The Top Shows chart is read up to 200 shows and each genre chart up to 200. Apple decides chart order; the actor does not re-rank it.
• Apple rate limits. Apple's public API allows roughly 20 requests per minute. The actor spaces its Apple requests and backs off on HTTP 403 and 429 with retries, so very large multi-country runs take a few minutes longer. Feed reads are not affected.
• Feed read limit. Each feed is read up to 400 KB. That always includes the newest episodes, so last-episode and cadence fields are accurate, but episodesInFeed then counts only the episodes read (feedTruncated: true). Use Apple's trackCount for the full catalog size.
• Broken feeds. When a feed is down, moved or not valid RSS, the row uses Apple's latest-release date (activitySource: apple) and feedStatus says why.
• Activity score is a heuristic. It measures publishing activity, not audience size or quality. Two shows with the same score can have very different audiences.
• Run time guard. The actor stops well before its timeout and keeps every row already delivered, so a run always ends as SUCCEEDED with partial results instead of failing.

Data source and license

Show metadata comes from Apple's public iTunes Search and Lookup APIs, the Apple Marketing Tools charts feed and Apple Podcasts genre charts. Activity comes from each show's public RSS feed, which the show publishes so that apps can list it. No login, cookies or API keys are used. Show names, descriptions and artwork belong to their creators; Apple Podcasts is a trademark of Apple Inc. This actor is independent and is not affiliated with or endorsed by Apple. Use artwork and descriptions in line with the rights of their owners, for example to identify a show in an internal list.

Related actors

• YouTube Sponsorship Tracker: find which brands sponsor which YouTube creators, the video version of a podcast sponsorship scan.
• YouTube Channel Scraper: channel stats and recent uploads, useful when a podcast also publishes on YouTube.
• YouTube Video Scraper: video-level details for podcast episodes posted as videos.

FAQ

Does it return podcast host emails or contact details? No. All email fields are removed from feeds, emails and phone numbers are removed from text, and any row containing an email address is dropped. Use the show's website to reach the team.

What counts as an active podcast? A show whose newest published episode is within activeWithinDays days of the run, 45 by default. Episodes scheduled in the future are ignored. Set onlyActive: false to receive every show with its activity numbers.

Why is a show's last episode newer than Apple's release date? Apple's directory refreshes on its own schedule. The actor reads the feed, which is the show's source of truth, so it often sees the newest episode first.

Can I get the Apple Podcasts charts for other countries? Yes. Put any two-letter Apple storefront code in countries, for example gb, de, br or jp, and pick all or a genre in chartGenres.

How is the activity score calculated? Recency of the last episode (45 points), cadence from the average gap between recent episodes (25), number of episodes in the last 90 days (15) and catalog depth from Apple's episode count (15). A weekly show that published this week scores in the 90s; a show silent for a year scores near zero.

Does it list individual episodes? It returns one row per show with the newest episode's date, title and duration plus counts. That keeps the schema flat and the price per show low.

How much does a typical run cost? $0.001 per show returned. 25 shows cost about $0.025, 1,000 shows about $1.00. Shows that do not match are not charged.

Can I refresh shows I already know? Yes. Paste Apple ids or Apple Podcasts URLs in appleIds. Ids are looked up 100 at a time.

Can I run it without reading feeds? Set includeFeedActivity: false for a fast Apple-only run. Activity then uses Apple's latest-release date and cadence fields are null.

Do I need an Apple or Podchaser account or API key? No. Only an Apify account.

Troubleshooting

• Zero results: your active window may be too short or your filters too strict. Check the run log, which lists how many shows were found, prefiltered and filtered out, and try activeWithinDays: 90 or remove language.
• Fewer rows than maxItems: search returns at most 200 shows per term; many of them may be inactive. Add terms, charts or countries.
• Many apple activity sources: some hosts block or slow feed requests. The row is still valid and uses Apple's date.
• A run takes longer than expected: large multi-country chart runs wait for Apple's rate limit. The guard still ends the run before its timeout with every delivered row kept.

Terms and responsible use

Use the data for research, sponsorship planning, booking and outreach that respects each show's own contact preferences. Do not use it for unsolicited bulk messaging. Do not republish artwork or descriptions as your own content.

Alternatives to Podcast Activity Tracker

You can search Apple Podcasts by hand and open each show's feed in a browser, which works for ten shows but not for two hundred. Paid podcast databases offer audience estimates and contact data under a subscription. General Apple Podcasts scrapers return directory metadata without checking whether a show is still publishing. This actor sits in between: pay per show, no subscription, activity measured from the feed and no personal data.

Use it from AI assistants (MCP)

Podcast Activity Tracker: Active Apple Podcasts & Charts works as a tool for AI assistants through the official Apify MCP server. Add this URL to any MCP client (Claude Desktop, Claude Code, Cursor, ChatGPT connectors, VS Code):

https://mcp.apify.com/?actors=transparent_meteorite/apple-podcasts-activity-tracker

{
  "mcpServers": {
    "apify": {
      "url": "https://mcp.apify.com/?actors=transparent_meteorite/apple-podcasts-activity-tracker",
      "headers": { "Authorization": "Bearer <YOUR_APIFY_TOKEN>" }
    }
  }
}

Then ask, for example: "Which of the top business podcasts published a new episode this week?"

Changelog

• 0.2 (2026-11-04): first public version. Apple search, Top Shows and 29 genre charts by country, Apple id lookup, streamed RSS activity with a 400 KB read limit, activity score, active-only filter, monitor mode, no-email enforcement, cost guard that ends runs early with partial results.

Support

Open an issue on the actor's Issues tab in Apify Console with your run id and the input you used. Feature requests are welcome, for example new chart types or extra activity fields.

Did this actor do the job? If it saved you time, a short honest review on the Reviews tab helps other people judge it. If something was off, open an Issue on this page with the input you used. I read every one and fix real bugs, usually the same day.