JioHotstar Scraper: Catalog URLs, Titles, Show & Episode IDs

JioHotstar Scraper turns the hotstar.com catalog into a clean dataset of shows, movies, episodes, sport pages, clips, channels, genres and languages. It reads the catalog dataset the platform itself publishes (the sitemap URL lists linked from its own robots.txt), so it needs no login and no session of any kind. Walk a whole catalog type page by page, or paste content URLs one at a time, then export to JSON, CSV or Excel, or pull the results straight into your app through the API. Recurring change tracking (what got added or removed) is built in.

Why This Scraper?

• One record per catalog URL. The row kind, humanized title, parent show title, show id and content id are all read straight from the URL the platform itself publishes for its index, so there is no guessing about what a page might contain.
• Walk the catalog by type. Episodes, shows, movies, sport landings, live pages, clips, channels, genres and languages are all selectable, and the episode surface alone carries hundreds of thousands of rows.
• Anonymous by design. The catalog list is public: no account, no session, no cookie jar. What sits behind a login (playback, descriptions, durations, reviews) is out of scope on purpose, so a run never fails because a session expired.
• Stable, resolvable identity. Every record is a real URL you or your own systems can revisit, join against, or fetch again later.
• Built for change tracking. Incremental mode remembers a previous walk of the same catalog scope: the first run returns everything as new, later runs return only what the platform added or dropped.
• Resume a capped or interrupted walk. Point a new run at a previous run id and it skips everything already collected there, so a very large catalog type does not have to be paid for twice.
• Optional MCP export. Pipe a summary of each record into Notion, Linear, Airtable or Apify without changing what lands in the dataset.

Use Cases

• Streaming catalog monitoring: track what the platform adds or removes, by show, movie or episode, on a recurring schedule.
• App and index builders: power your own search or deep-link feature with a lightweight id and title index instead of maintaining your own catalog crawl.
• Content research and archiving: build a historical record of what was listed, and when a title disappeared from the catalog.
• Catalog QA teams: confirm that a newly published show or episode URL is actually listed in the site's own catalog before announcing it elsewhere.
• Data pipelines and joins: feed stable show and content ids into a downstream system that already tracks the same titles by name.

Data You Get

Sample shape: values are illustrative placeholders, not from a live listing.

Field	Example
recordId	"1000200000" (the episode, show or movie's own numeric id)
recordId (no numeric segment)	"slug:cricket" (sport, genre, language and channel landing pages)
url	the catalog URL itself, kept exactly as published
kind	"episode" (also "show", "movie", "sport", "clip", "channel", "genre", "language", "live_tv")
title (episode row)	"Sample Episode Title"
title (show or movie row)	"Sample Show Name" (the show's or movie's own title)
showTitle (episode row)	"Sample Show Name" (the parent show)
showTitle (show or movie row)	same value as title, no separate parent
showId (episode row)	"500000" (the parent show's numeric id)
showId (show or movie row)	same value as contentId, no separate parent
contentId	"1000200000" (the row's own numeric id, same value as recordId)
scrapedAt	"2026-01-01T00:00:00Z"
changeType	"NEW" (also "UPDATED", "UNCHANGED", "REAPPEARED", "EXPIRED"; incremental mode only)
changedFields	[] (incremental mode only)
firstSeenAt	"2026-01-01T00:00:00Z" (incremental mode only)
lastSeenAt	"2026-01-01T00:00:00Z" (incremental mode only)

changedFields, firstSeenAt and lastSeenAt are populated only when Incremental mode is on. Landing-page URLs with no numeric id segment (for example a sport, genre or language landing) get a slug: record id and carry null for showTitle, showId and contentId.

How to Use

1. Pick a mode: sitemap (walk a catalog type) or url (paste content links).
2. In sitemap mode, choose a catalog type; in URL mode, paste one or more catalog URLs.
3. Set Max items (and, in sitemap mode, optionally Max maps per run) to control run size and cost.
4. Click Start, then download the dataset as JSON, CSV or Excel, or read it through the API.

Walk the episode catalog (the default):

{
  "mode": "sitemap",
  "mapType": "EPISODE",
  "maxItems": 50
}

A different catalog type:

{
  "mode": "sitemap",
  "mapType": "SHOWS",
  "maxItems": 100
}

Paste catalog URLs:

{
  "mode": "url",
  "urls": [
    "https://www.hotstar.com/in/shows/sample-show/500000",
    "https://www.hotstar.com/in/movies/sample-movie/500001"
  ]
}

Daily change watch of a mapped catalog surface:

{
  "mode": "sitemap",
  "mapType": "EPISODE",
  "maxItems": 0,
  "incrementalMode": true,
  "emitExpired": true
}

Run it from your code

Python:

from apify_client import ApifyClient

client = ApifyClient("<YOUR_APIFY_TOKEN>")
run = client.actor("abotapi/hotstar-com-scraper").call(run_input={"mode": "sitemap", "mapType": "SHOWS", "maxItems": 50})
for record in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(record["kind"], record["title"], record["url"])

JavaScript:

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: '<YOUR_APIFY_TOKEN>' });
const run = await client.actor('abotapi/hotstar-com-scraper').call({ mode: 'sitemap', mapType: 'SHOWS', maxItems: 50 });
const { items } = await client.dataset(run.defaultDatasetId).listItems();

Or connect it to Make, Zapier, n8n, Google Sheets or webhooks from the Integrations tab.

How Max items and Max maps shape a sitemap walk

The episode surface alone holds hundreds of thousands of rows spread across about 10 catalog map files. A run walks map files in order and stops once Max items is reached; set it to 0 to walk every map file for that catalog type. Max maps per run is a separate, optional safety bound on how many map files to download in one run, useful for spreading a very large catalog type across several runs; leave it at 0 to let Max items be the only limit.

Resume and recurring updates

• Resume (resumeFromRunId) continues one interrupted or capped run: paste its run or dataset id and this run skips everything already collected there, so you don't pay twice for the same catalog type.
• Incremental mode (incrementalMode) is for walking the same catalog scope again and again, for example daily. Each record is classified NEW, REAPPEARED or EXPIRED against the previous walk (the catalog is static per URL, so a previously seen row never reports UPDATED unless its title text itself changed). UNCHANGED rows are suppressed and not billed unless emitUnchanged is on; EXPIRED rows are only produced after a run that scanned the whole scope with no cap, and only with emitExpired on. In sitemap mode, Max items counts every catalog row the run reads, including unchanged ones it does not return, so set it to 0 for a change watch; a smaller value only ever re-checks the first rows of the catalog type. stateKey names or shares the stored state; leave it empty and the actor derives one automatically from the mode, catalog type and URLs, so two different walks never mix state. Do not reuse one stateKey across different catalog types or URL lists with emitExpired on: each walk would report the other walk's rows as removed.

Send results into your apps (MCP connectors)

Optional: the run pipes a condensed summary per record (title, kind, URL) into a connector you authorize under Apify, Settings, API and Integrations. This is an extra delivery step after the scrape; the Apify dataset is never changed.

1. Authorize a connector once under Apify -> Settings -> Integrations (Notion, Linear, Airtable, or Apify).
2. Select it in the "Pipe results into your apps" input field. (If the picker is empty, you haven't authorized a connector yet.)
3. For Notion, also set notionParentPageUrl to the page where records should be created.

Each connector receives a condensed summary per record, not the full record; the complete record always stays in the Apify dataset. Set maxNotifyListings to cap how many records flow per connector per run. Leave mcpConnectors empty to skip this entirely, which never changes what the dataset returns.

Input Parameters

Parameter	Type	Default	Description
mode	string	sitemap	sitemap walks the site's own published catalog lists. url processes pasted catalog URLs.
mapType	string	EPISODE	Sitemap mode only: which catalog dataset to walk (EPISODE, SHOWS, MOVIE, SPORT and the rest of the site's own catalog types).
urls	array	(none)	URL mode only: hotstar.com catalog URLs. Each pasted URL returns one record.
maxItems	integer	20	Stop after collecting this many records across all catalog maps and URLs. 0 = unlimited.
maxPages	integer	0	Safety bound on how many catalog map files (each up to 50,000 rows) to download per run. 0 = no map limit; the run then stops at Max items instead.
resumeFromRunId	string	(none)	Continue one interrupted or capped run from its previous run id or dataset id.
incrementalMode	boolean	false	Recurring monitoring of the same catalog walk: later runs return only what changed (NEW, plus EXPIRED and REAPPEARED when Emit expired is on) instead of the full snapshot.
stateKey	string	(none)	Optional name for the incremental state. Leave empty to get a separate state per mode, catalog type and URL list; set it only to name a campaign or deliberately share state.
emitUnchanged	boolean	false	Incremental mode only: also return (and bill) rows that have not changed, marked UNCHANGED.
emitExpired	boolean	false	Incremental mode only: also return (and bill) rows the previous run tracked that are no longer in the mapped catalog. Only after a complete, uncapped scan.
mcpConnectors	array	(none)	Optional: send a summary of each record to apps you authorized under Integrations.
notionParentPageUrl	string	(none)	Notion connector only: page under which record pages are created.
maxNotifyListings	integer	50	Cap on records written to each connector per run. Does not affect the dataset.
proxy	object	India residential	Connection settings. The catalog answers an India connection, so the default pins an India exit.

Output Example

Sample shape: values are illustrative placeholders, not from a live listing.

{
  "recordId": "1000200000",
  "url": "https://www.hotstar.com/in/shows/sample-show/500000/sample-episode-title/1000200000/watch",
  "kind": "episode",
  "title": "Sample Episode Title",
  "showTitle": "Sample Show Name",
  "showId": "500000",
  "contentId": "1000200000",
  "scrapedAt": "2026-01-01T00:00:00Z"
}

Plan Requirement

The default connection pins an India residential exit, which this catalog requires to answer at all. Leave it as is unless a run reports that it could not read any results; try again, since the shared pool rotates, or use a custom proxy endpoint of your own.

FAQ

How much does it cost?

You pay per record returned. The Pricing tab shows the current rates. Use Max items to cap the cost of any run.

Is it legal to scrape JioHotstar?

This actor reads only the catalog URL list the platform itself publishes in its sitemap, advertised in its own robots.txt. You are responsible for how you use the results: follow the platform's terms and the laws that apply to you, and get legal advice if you plan commercial redistribution.

Can I get only new or removed titles on a schedule?

Yes. Schedule the actor from the Schedules tab and turn on Incremental mode, with Emit expired records on if you also want to know what was removed. Unchanged rows are not billed.

Why does this actor not return descriptions, durations or ratings?

Those fields sit behind the platform's own session gate (a signup flow this actor does not fake), and the public page shell serves an empty template to automated readers. This actor reads the catalog index only: the row kind, title, show and ids, all taken from the URL itself.

Why did my pasted URL come back empty?

URL mode only understands catalog content pages (shows, movies, episodes, sport, clips, channels, genres, languages). Account pages and the site's search results are not catalog URLs and are reported as unread rather than guessed at.

Why did my run fail instead of returning an empty dataset?

If the site refuses every request, the run stops with a clear message so "nothing in this catalog type" is never confused with "nothing could be read". Run it again in a few minutes. If only some catalog map files could not be read, you still get what was found.

Can I use it with AI agents or MCP?

Yes. Call it from any Apify integration or MCP client, and use the connector field to push results into Notion, Linear or Airtable.

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