IMDb Scraper — Extract Movie & TV Ratings, Charts, Cast & Box Office Data

Scrape IMDb titles by keyword, chart, or URL — ratings with vote counts, genres, plots, runtimes, and posters. No coding required.

Type a keyword (or pick a chart, or paste any IMDb URL), click Start, and get one clean JSON record per title: IMDb rating with vote count, type (movie/TV), release year, runtime, plot, genres, poster image, and the direct IMDb link. Filter searches server-side by type, genre, and release-year range, sorted by popularity, rating, votes, release date, or alphabetically — across IMDb's 11 million+ titles.

Need everything? Turn on Scrape Full Title Details and every title also comes with its Metascore, certificate, exact release date, Top 250 rank, directors, creators, writers, and stars with their IMDb IDs, top cast with character names and headshots, total cast count, trailer, box office (budget, opening weekend, worldwide gross), similar titles, countries of origin, and spoken languages.

It scrapes IMDb charts in one click too — the full Top 250 Movies and Top 250 TV Shows, the 100 Most Popular movies and shows (with weekly rank changes), the weekend box office with grosses, and the 100 most popular celebrities (StarMeter). And it takes IMDb URLs: advanced-search URLs are scraped with their embedded filters, chart URLs as charts, and title page URLs always return the fully-detailed record.

All this at $1 per 1,000 titles — the lowest price on the Apify Store, with no start fee and no monthly rental.

Rated Excellent — 4.6 based on 25 reviews on Trustpilot.

Output example: IMDb title data in JSON

Each title becomes one dataset item. Here is a search result row:

{
  "query": "avengers",
  "id": "tt4154796",
  "title": "Avengers: Endgame",
  "link": "https://www.imdb.com/title/tt4154796/",
  "type": "movie",
  "is_series": false,
  "year": 2019,
  "runtime_minutes": 181,
  "plot": "After the devastating events of Avengers: Infinity War (2018), the universe is in ruins...",
  "genres": ["Action", "Adventure", "Sci-Fi"],
  "rating": { "value": 8.4, "vote_count": 1480471 },
  "image": {
    "link": "https://m.media-amazon.com/images/M/MV5BMTc5MDE2ODcwNV5BMl5BanBnXkFtZTgwMzI2NzQ2NzM@._V1_.jpg",
    "width": 1382,
    "height": 2048
  }
}

With Scrape Full Title Details on (and always for title page URLs), the same record grows into the full profile:

{
  "release_date": "2019-04-26",
  "certificate": "PG-13",
  "rating": { "value": 8.4, "vote_count": 1480430, "top_rank": 74 },
  "metascore": { "score": 78, "review_count": 57 },
  "directors": [
    { "id": "nm0751577", "name": "Anthony Russo", "link": "https://www.imdb.com/name/nm0751577/" },
    { "id": "nm0751648", "name": "Joe Russo", "link": "https://www.imdb.com/name/nm0751648/" }
  ],
  "stars": [
    { "id": "nm0000375", "name": "Robert Downey Jr.", "link": "https://www.imdb.com/name/nm0000375/" }
  ],
  "top_cast": [
    {
      "id": "nm0000375",
      "name": "Robert Downey Jr.",
      "characters": ["Tony Stark", "Iron Man"],
      "image": { "link": "https://m.media-amazon.com/images/M/....jpg" }
    }
  ],
  "total_cast": 169,
  "trailer": { "id": "vi2163260441", "link": "https://www.imdb.com/video/vi2163260441/", "duration_seconds": 66 },
  "box_office": {
    "budget": { "amount": 356000000, "currency": "USD" },
    "opening_weekend": { "amount": 357115007, "currency": "USD" },
    "gross_worldwide": { "amount": 2799439100, "currency": "USD" }
  },
  "countries_of_origin": ["United States"],
  "spoken_languages": ["English", "Japanese", "Xhosa", "German"]
}

Trimmed for readability. You can download the dataset as JSON, CSV, Excel, XML, or an HTML table.

What data does the IMDb Scraper extract?

Data group	Fields
Title	Name, original title, IMDb link and tt-id, type (movie/TV/series flag), release year(s), runtime, plot, genres, poster with dimensions
Reputation	IMDb rating and vote count, Top 250 rank, Metascore with review count (detailed mode)
Charts	Chart name, rank, weekly rank change (popularity charts), weekend + worldwide grosses (box office), StarMeter data for celebrities
People (detailed mode)	Directors, creators, writers, stars — each with IMDb nm-id and link; top cast with character names and headshots; total cast size
Release & business (detailed mode)	Exact release date, certificate, box office budget / opening weekend / US & worldwide gross, trailer link
Context (detailed mode)	Similar titles, countries of origin, spoken languages

How to scrape IMDb data

1. Click Try for free.
2. Type one or more keywords and set filters (movies/TV, genre, year range, sort). Or tick charts — Top 250s, Most Popular, Weekend Box Office, Popular Celebrities. Or paste IMDb URLs: search URLs keep their embedded filters, title page URLs return one detailed record each.
3. Optionally turn on Scrape Full Title Details for the complete profile per title.
4. Click Start and wait for the run to finish.
5. Open the Dataset tab to preview your data, then download it as JSON, CSV, Excel, XML, or an HTML table.

No proxies, no browser setup, no CAPTCHA solving — you type a keyword and get structured data back.

Input

{
  "searchQueries": ["avengers"],
  "charts": ["top-movies", "box-office"],
  "startUrls": [
    "https://www.imdb.com/search/title/?genres=sci-fi&sort=user_rating,desc",
    "https://www.imdb.com/title/tt4154796/"
  ],
  "type": "movie",
  "genre": "Sci-Fi",
  "startYear": 2010,
  "endYear": 2026,
  "sortBy": "popularity",
  "maxResultsPerSearch": 100,
  "scrapeTitleDetails": false,
  "country": "US"
}

Field	Type	Description
searchQueries	array	Keywords matched against title names — each searched separately across 11M+ titles.
charts	array	Any of top-movies, top-tv, popular-movies, popular-tv, box-office, popular-celebrities.
startUrls	array	IMDb URLs — advanced-search URLs (embedded filters override the fields below), chart URLs, and/or title page URLs (always scraped with full details).
type / genre	string	Movies or TV only; one of 27 genres.
startYear / endYear	integer	Release-year range.
sortBy	string	popularity (default), rating, vote_count, release_date, alphabetical.
maxResultsPerSearch	integer	Max titles per keyword, URL, or chart (default 100). Controls your cost.
scrapeTitleDetails	boolean	Off by default. When enabled, every result also gets the full profile — Metascore, cast, box office, trailer, similar titles.
country	string	2-letter code localizing release dates, certificates, and regional titles (default US).

How much does it cost to scrape IMDb?

Scraping IMDb costs $1 per 1,000 titles ($0.001 per title) — the lowest price on the Apify Store, with no Actor start fee and no monthly rental (the incumbents charge $35–$50/month before you scrape anything).

With Scrape Full Title Details on (and for title page URLs), each title — Metascore, full cast credits, box office, trailer, similar titles — is billed at $2.50 per 1,000 detailed titles in total. Every row is billed at exactly one rate — standard or detailed — and the detailed rate applies only when the full details are actually returned.

Apify gives you $5 in free credits every month, so you can scrape your first 5,000 titles (or 2,000 fully-detailed titles) free and test the IMDb Scraper before paying anything.

FAQs

Why scrape IMDb?

• Content research & licensing — map what exists in any genre/year range with ratings and vote counts as demand signals.
• Streaming & media apps — feed recommendation engines, watchlist tools, and catalogs with structured title data including posters and trailers.
• Market analysis — track the box office weekend by weekend, watch popularity charts move with weekly rank changes, benchmark against the Top 250.
• Data science — clean JSON with ratings, votes, Metascores, runtimes, and box-office numbers, ready for analysis.

Can I scrape an IMDb search URL?

Yes. Paste any imdb.com/search/title/?… URL from your browser and the Actor reads the filters embedded in it — title type, genres, release-date range, and sort order — and applies them automatically. URL parameters take priority over the form fields. Chart URLs (imdb.com/chart/top, boxoffice, …) and imdb.com/find search URLs work too.

What does "Scrape Full Title Details" add?

The complete title profile: Metascore, certificate, exact release date, Top 250 rank, directors/creators/writers/stars with IMDb IDs, top cast with character names and headshots, total cast count, trailer link, box office (budget, opening weekend, worldwide gross), similar titles, countries of origin, and spoken languages. Title page URLs pasted into startUrls always include these details.

Can I scrape the Top 250 in one run?

Yes — tick Top 250 Movies (or TV) and all 250 rows arrive from a single call, each with its rank. The whole chart costs $0.25 at the standard rate. Popularity charts include the weekly rank change; the box-office chart includes weekend and worldwide grosses.

Will I be charged twice if the same title appears in two searches?

No. Titles are deduplicated per run — a title matching several keywords, charts, or URLs is scraped and billed only once. Every row is billed at exactly one rate: $1/1,000 standard or $2.50/1,000 detailed. And if a full-details fetch fails, you keep the card row and pay only the standard rate for it.

How accurate is the scraped IMDb data?

It comes straight from live IMDb pages — real ratings and vote counts, current chart ranks, this weekend's box office, in the same structure you see on the site.

Is it legal to scrape IMDb?

The Actor extracts publicly available data only — titles, ratings, and charts visible to any visitor. It collects no personal data behind logins. You are responsible for how you use the data; consult a lawyer if unsure about your use case.

Need user reviews too?

Use our IMDb Reviews Scraper — feed it the link values from this Actor's output and get full user reviews with ratings, review text, helpful votes, and spoiler flags, at $1 per 1,000 reviews.

Support

Built by developers, for developers — when you reach out, you talk to the engineers who built the Actor, not a support script. Message us anytime and we'll resolve your query within 1 working day.

Email: happy.to.help@omkar.cloud

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