The Movie Data Recommender API is designed for developers, entertainment platforms, and audiovisual content applications that seek to offer personalized experiences to their users. Through its advanced search and analysis technology, the API provides detailed results on thousands of movies, including key information such as title, synopsis, release date, genres, original language, average rating, number of reviews, popularity, and visual resources such as posters and promotional backgrounds.
Its intelligent recommendation engine is based on semantic matches, popularity analysis, and thematic affinities, ensuring relevant results even with partial or imprecise queries. For example, a search for “The God” can return iconic films such as The Godfather, along with others related by theme or keyword. In this way, users can discover both cinema classics and recent releases, expanding their viewing options according to their interests.
In addition, the API provides a constantly updated trends endpoint, which returns the most popular movies of the moment based on audience interaction, critic ratings, and global popularity metrics. This allows platforms to integrate real-time “trending titles” or “most viewed” lists, offering fresh and relevant content.
The API response is delivered in structured JSON format, making it easy to integrate with websites, mobile apps, or streaming services. Each item includes unique identifiers, image paths, and popularity data that can be used to create visually appealing and dynamic interfaces.
Overall, the Movie Data Recommender API is a versatile and efficient solution for those who want to enrich their projects with accurate movie information, personalized recommendations, and trend analysis, ensuring a smooth, modern, and data-driven experience.
Get accurate and relevant results from any title you search for.
Search Movies - Endpoint Features
| Object | Description |
|---|---|
q |
[Required] Enter the name of a movie |
{"success":true,"query":"the godfather","movies":[{"id":111,"title":"Scarface","release_date":"1983-12-09","overview":"After getting a green card in exchange for assassinating a Cuban government official, Tony Montana stakes a claim on the drug trade in Miami. Viciously murdering anyone who stands in his way, Tony eventually becomes the biggest drug lord in the state, controlling nearly all the cocaine that comes through Miami. But increased pressure from the police, wars with Colombian drug cartels and his own drug-fueled paranoia serve to fuel the flames of his eventual downfall.","genre_ids":[28,80,18],"vote_average":8.16,"vote_count":12483,"popularity":14.8939,"poster_path":"/iQ5ztdjvteGeboxtmRdXEChJOHh.jpg","backdrop_path":"/sctvs9cUwJD15qlTlrsh2BXsK75.jpg","adult":false,"original_language":"en","original_title":"Scarface"},{"id":769,"title":"GoodFellas","release_date":"1990-09-12","overview":"The true story of Henry Hill, a half-Irish, half-Sicilian Brooklyn kid who is adopted by neighbourhood gangsters at an early age and climbs the ranks of a Mafia family under the guidance of Jimmy Conway.","genre_ids":[18,80],"vote_average":8.455,"vote_count":13672,"popularity":12.0468,"poster_path":"/aKuFiU82s5ISJpGZp7YkIr3kCUd.jpg","backdrop_path":"/sw7mordbZxgITU877yTpZCud90M.jpg","adult":false,"original_language":"en","original_title":"GoodFellas"},{"id":1422,"title":"The Departed","release_date":"2006-10-04","overview":"To take down South Boston's Irish Mafia, the police send in one of their own to infiltrate the underworld, not realizing the syndicate has done likewise. While an undercover cop curries favor with the mob kingpin, a career criminal rises through the police ranks. But both sides soon discover there's a mole among them.","genre_ids":[18,53,80],"vote_average":8.159,"vote_count":15579,"popularity":10.4181,"poster_path":"/nT97ifVT2J1yMQmeq20Qblg61T.jpg","backdrop_path":"/6WRrGYalXXveItfpnipYdayFkQB.jpg","adult":false,"original_language":"en","original_title":"The Departed"},{"id":311,"title":"Once Upon a Time in America","release_date":"1984-05-23","overview":"A former Prohibition-era Jewish gangster returns to the Lower East Side of Manhattan over thirty years later, where he once again must confront the ghosts and regrets of his old life.","genre_ids":[18,80],"vote_average":8.405,"vote_count":5751,"popularity":7.8004,"poster_path":"/i0enkzsL5dPeneWnjl1fCWm6L7k.jpg","backdrop_path":"/uPYa165sraN2c8gZBM9C47g3JoU.jpg","adult":false,"original_language":"en","original_title":"Once Upon a Time in America"},{"id":4982,"title":"American Gangster","release_date":"2007-11-02","overview":"Loosely based on the criminal career of Frank Lucas, a gangster from La Grange, North Carolina, who smuggled heroin into the United States on American service planes returning from the Vietnam War, before being detained by a task force led by Newark Detective Richie Roberts.","genre_ids":[18,80],"vote_average":7.59,"vote_count":5745,"popularity":7.3892,"poster_path":"/8sV6nWuKczuXRt0C6EWoXqJAj6G.jpg","backdrop_path":"/dLL90vskYFn1S89RZp5TUguK9wl.jpg","adult":false,"original_language":"en","original_title":"American Gangster"},{"id":117,"title":"The Untouchables","release_date":"1987-06-03","overview":"Elliot Ness, an ambitious prohibition agent, is determined to take down Al Capone. In order to achieve this goal, he forms a group given the nickname “The Untouchables”.","genre_ids":[80,36,53],"vote_average":7.757,"vote_count":5941,"popularity":6.6346,"poster_path":"/8BquGK22zCcsmBWiaIakaaPpSZb.jpg","backdrop_path":"/qJbMgG2ZkWOk7zdMfC4JVfEk10N.jpg","adult":false,"original_language":"en","original_title":"The Untouchables"},{"id":524,"title":"Casino","release_date":"1995-11-22","overview":"In early-1970s Las Vegas, Sam \"Ace\" Rothstein gets tapped by his bosses to head the Tangiers Casino. At first, he's a great success in the job, but over the years, problems with his loose-cannon enforcer Nicky Santoro, his ex-hustler wife Ginger, her con-artist ex Lester Diamond and a handful of corrupt politicians put Sam in ever-increasing danger.","genre_ids":[80,18],"vote_average":7.993,"vote_count":6196,"popularity":6.5489,"poster_path":"/gziIkUSnYuj9ChCi8qOu2ZunpSC.jpg","backdrop_path":"/iZGiMD0p1M2AOmzKknFo5bkuz94.jpg","adult":false,"original_language":"en","original_title":"Casino"},{"id":9654,"title":"The Italian Job","release_date":"2003-05-30","overview":"Charlie Croker pulled off the crime of a lifetime. The one thing that he didn't plan on was being double-crossed. Along with a drop-dead gorgeous safecracker, Croker and his team take off to re-steal the loot and end up in a pulse-pounding, pedal-to-the-metal chase that careens up, down, above and below the streets of Los Angeles.","genre_ids":[28,80],"vote_average":6.784,"vote_count":5765,"popularity":6.2787,"poster_path":"/eSkjK4kctyrWpFhxl35GPvSs6tI.jpg","backdrop_path":"/haIHcieOlTlyAUr9cWukqyK5SaU.jpg","adult":false,"original_language":"en","original_title":"The Italian Job"},{"id":6075,"title":"Carlito's Way","release_date":"1993-11-10","overview":"Free after years in prison, Carlito Brigante intends to give up his criminal ways, but it's not long before the ex-con is sucked back into the New York City underworld. Reconnecting with his dancer girlfriend, Carlito gets entangled in the shady dealings of his friend Dave Kleinfeld, who also serves as his lawyer. An encounter with shifty gangster Benny Blanco sets the duo on a dangerous path.","genre_ids":[80,18,53],"vote_average":7.829,"vote_count":3317,"popularity":5.1834,"poster_path":"/g6D7mjQtndu768cusGmoEQY9fTB.jpg","backdrop_path":"/38yjZWYBI0xxNqoBKiGyA4UZjk.jpg","adult":false,"original_language":"en","original_title":"Carlito's Way"},{"id":9366,"title":"Donnie Brasco","release_date":"1997-02-27","overview":"An FBI undercover agent infiltrates the mob and identifies more with the mafia life at the expense of his regular one.","genre_ids":[80,18,53],"vote_average":7.535,"vote_count":4650,"popularity":4.8461,"poster_path":"/xtKLvpOfARi1XVm8u2FTdhY5Piq.jpg","backdrop_path":"/6a6AK1pANcl64BYeDA58HKqgzji.jpg","adult":false,"original_language":"en","original_title":"Donnie Brasco"}],"total":10,"requestId":"5ea80a5a-8e5c-485f-8162-3e88dbecde16","timestamp":"2025-10-06T20:07:33.895Z","version":"1","log":"-"}
curl --location --request GET 'https://zylalabs.com/api/10664/movie+data+recommender+api/20216/search+movies?q=the godfather' --header 'Authorization: Bearer YOUR_API_KEY'
Get the most popular movies of the moment with details such as title, synopsis, date, rating, language, genres, and images.
{"Example Response":"No response example available for now."}
curl --location --request GET 'https://zylalabs.com/api/10664/movie+data+recommender+api/20221/trendings' --header 'Authorization: Bearer YOUR_API_KEY'
| Header | Description |
|---|---|
Authorization
|
[Required] Should be Bearer access_key. See "Your API Access Key" above when you are subscribed. |
No long-term commitment. Upgrade, downgrade, or cancel anytime. Free Trial includes up to 50 requests.
The "Search Movies" endpoint returns detailed information about movies matching a search query, including title, release date, overview, genres, ratings, and popularity. The "Trendings" endpoint provides data on the most popular movies, including similar fields such as title, synopsis, rating, and images.
Key fields in the response data include "id," "title," "release_date," "overview," "genre_ids," "vote_average," "vote_count," "popularity," "poster_path," and "backdrop_path." These fields provide essential details for each movie.
The "Search Movies" endpoint allows users to input a title query. The "Trendings" endpoint does not require parameters, as it automatically returns the most popular movies based on current trends.
The response data is structured in JSON format. For "Search Movies," it includes a success flag, the query, and an array of movie objects. Each movie object contains fields like title, release date, and ratings, making it easy to parse and display.
The Movie Data Recommender API aggregates data from various film databases and industry sources to ensure comprehensive coverage of movies, including both classic and recent releases, maintaining a broad and diverse dataset.
Typical use cases include integrating personalized movie recommendations into streaming platforms, creating trending movie lists for entertainment apps, and enhancing user engagement through tailored movie discovery experiences.
Users can utilize the returned data to create dynamic interfaces, display movie details, and generate personalized recommendations. For example, using the "poster_path" and "backdrop_path" fields, developers can enhance visual appeal in their applications.
If a search query returns partial or empty results, users can refine their queries by using broader terms or checking for spelling errors. The API's intelligent recommendation engine may also suggest related titles based on semantic matches.
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