Find Your Next Movie After a Favorite
Start from one movie you already love and turn it into a shortlist of films with similar tone, genre, and audience response.
Similar Movies
Find the next movie with the same energy
Turn one favorite movie or a small set of seed titles into a ranked shortlist of genuinely similar films. Great for watchlist building, movie-night planning, and agents that need explainable recommendations instead of generic search results.
Find Similar
Resolve one movie title or TMDb id and return a ranked shortlist of similar films with clear match reasons and alternate seed matches when the title is ambiguous.
Returns: A resolved seed movie plus a paginated shortlist of similar films with match scores and human-readable reasons
Parameters
titlestringMovie title to resolve, such as "Inception" or "The Prestige"
tmdb_idnumberOptional TMDb movie id for an exact seed lookup
yearnumberOptional release year to disambiguate the seed title
strategystringRanking source: blended uses both recommendations and similar titles, recommendations uses TMDb recommendations only, similar uses TMDb similar only
include_same_collectionbooleanWhen false, exclude movies from the same TMDb collection or franchise where possible
min_vote_averagenumberOptional minimum TMDb vote average for returned movies, from 0 to 10
languagestringOptional TMDb language code for localized titles and overviews, such as en-US or fr-FR
limitnumberMaximum movies to return per page (1-20, default 10)
pagenumberResult page number for the ranked shortlist (default 1)
Example
Find movies similar to Inception without returning the same franchise
curl -H "Authorization: Bearer $TOOLROUTER_API_KEY" \
-d '{
"tool": "similar-movies",
"skill": "find_similar",
"input": {
"title": "Inception",
"include_same_collection": false,
"limit": 8
}
}' \
https://api.toolrouter.com/v1/tools/callBlend Taste
Blend recommendations from multiple seed movies into one ranked shortlist so you can discover films that sit at the intersection of several favorites.
Returns: A blended, paginated shortlist built from multiple seed movies, including matched seeds, excluded titles, and explainable reasons
Parameters
titlesarraySeed movie titles to blend together, using two to five favorites for the strongest results
tmdb_idsarrayOptional exact TMDb movie ids to use as seeds instead of title resolution
avoid_titlesarrayOptional movie titles to exclude from the final shortlist
avoid_tmdb_idsarrayOptional exact TMDb ids to exclude from the final shortlist
include_same_collectionbooleanWhen false, exclude movies from the same TMDb collection or franchise where possible
min_vote_averagenumberOptional minimum TMDb vote average for returned movies, from 0 to 10
languagestringOptional TMDb language code for localized titles and overviews, such as en-US or es-ES
limitnumberMaximum movies to return per page (1-20, default 10)
pagenumberResult page number for the ranked shortlist (default 1)
Example
Blend Inception and Arrival into one sci-fi shortlist
curl -H "Authorization: Bearer $TOOLROUTER_API_KEY" \
-d '{
"tool": "similar-movies",
"skill": "blend_taste",
"input": {
"titles": [
"Inception",
"Arrival"
],
"include_same_collection": false,
"limit": 8
}
}' \
https://api.toolrouter.com/v1/tools/callQuick Start
MCP (Claude Code)
claude mcp add --transport stdio \
--env TOOLROUTER_API_KEY=YOUR_API_KEY \
toolrouter -- npx -y toolrouter-mcpREST API
curl -H "Authorization: Bearer $TOOLROUTER_API_KEY" \
-d '{"tool":"similar-movies","skill":"find_similar","input":{}}' \
https://api.toolrouter.com/v1/tools/callUse Cases
Blend Several Favorite Movies Into One Shortlist
Combine two to five seed movies and rank the films that sit at the intersection of those tastes instead of following only one reference title.
Search Papers by Topic
Find relevant academic papers on any research topic across millions of scholarly publications.
Geocode Addresses to Coordinates
Convert street addresses into precise latitude and longitude coordinates for mapping and spatial analysis.
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 “movies 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.