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Similar Movies

Find the next movie with the same energy

Similar Movies turns one film you loved into a ranked shortlist of what to watch next. Skip the endless scroll β€” give it a title and get back genuinely similar movies with clear reasons why each one matches.

It works from the specific things that made a film work: tone, genre, era, and narrative structure. You can start from a single movie or blend two to five seeds to find films that sit at an unusual intersection of tastes.

What you can do

  • Find movies similar to a single title, ranked by how closely they match
  • Blend two to five seed movies and get a shortlist that combines all of those tastes
  • Filter out franchise sequels when you want fresh alternatives
  • Set a minimum rating threshold to keep quality high
  • Browse deeper results with pagination

Who it's for

Anyone building a watchlist or planning movie night. Recommendation apps that need explainable suggestions rather than black-box results. Agents that need to answer "what should I watch next" with real reasoning.

How to use it

  1. Use find_similar with a movie title to get a ranked list of similar films β€” add a release year if the title is ambiguous
  2. Use blend_taste with two to five seed titles to find films at the intersection of those tastes
  3. Set include_same_collection to false if you want fresh picks instead of sequels and prequels
  4. Use min_vote_average to filter out low-rated results, and page to browse deeper

Getting started

Connect your movie database account to unlock recommendations β€” search by title and you're ready to go.

Information

Price
Free
Provider
TMDb
TMDb API Key
API key or read-access token for The Movie Database search and recommendation endpoints Β· Get key

Frequently Asked Questions

What is the difference between find_similar and blend_taste?

`find_similar` starts from one seed movie, while `blend_taste` merges recommendations from several seed films into one shortlist. Use the single-seed flow for a straightforward β€œmovies like this” request and the blend flow when the taste brief is really an intersection of two or more favorites.

Do I need an exact TMDb id before using the tool?

No. You can pass a normal movie title and the tool will resolve the best seed match for you. If a title is ambiguous, the response also includes alternate seed matches so you can see what else it considered.

Can I avoid sequels or same-franchise recommendations?

Yes. Set `include_same_collection` to `false` to filter out movies from the same TMDb collection where the API exposes that relationship. This is useful when you want adjacent films rather than the obvious sequel list.

Can I exclude a movie I have already seen from the final shortlist?

Yes. `blend_taste` accepts `avoid_titles` and `avoid_tmdb_ids`, so you can remove obvious or already-watched picks from the results before you review the final ranking.

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