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tmdb-mcp
by wsqreis

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      Enables AI assistants to search movies and TV shows, compare ratings across multiple sources, check streaming availability, and manage lists, watchlists, ratings, and watch history through natural language.
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    • A
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      Enables movie and TV lookups through twelve read-only tools: title and person search, full details, episode lists, discovery by genre/year/language/streaming service, trending and recommendations, where to watch by country, and merged critic/audience scores from IMDb, Rotten Tomatoes, Metacritic, Letterboxd and others. Runs as a local stdio server or a containerized Streamable HTTP service with bearer auth.
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      Enables AI agents to search IMDb titles, retrieve detailed metadata and ratings, list top-rated titles with filters, and browse TV series episodes with per-episode ratings and crew information.
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    • A
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      Provides integration with The Movie Database (TMDB) API for searching movies, TV shows, and people, accessing detailed information, and discovering popular and trending content. Enables AI assistants to access comprehensive movie and television metadata including ratings, cast, crew, and overviews.
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    • A
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      Enables MCP clients such as Claude, Cursor, and VS Code to search movie and TV titles, read full records for movies, TV shows, seasons, and people, check trending lists, discover titles, and find cinema showtimes.
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    TDQS

    A3.9/5.0

    Scored across 10 tools

    Disambiguation5/5

    Each tool targets a distinct intent: search_* tools find by name for a specific resource type, discover browses by filters, and the get_* tools each retrieve details for a specific resource. discover vs search_movies and get_recommendations vs discover are the closest overlap but descriptions clearly delineate criteria-based browsing from name lookup and 'more like X' requests.

    Naming Consistency4/5

    Consistent verb_noun pattern across search_movies, search_tv_shows, search_people, get_movie_details, get_tv_show_details, get_person_details, get_watch_providers, get_trending, and get_recommendations. The lone outlier is the bare-verb 'discover', a minor deviation.

    Tool Count5/5

    Ten tools is well-scoped for a media discovery domain, with search, details, discovery, trending, recommendations, and availability each earning a distinct slot without redundancy.

    Completeness4/5

    The surface covers the core lifecycle: finding titles/people, browsing by filters, fetching details, watching providers, trending, and recommendations. Minor gaps exist around season/episode-level detail and collection/list operations, but agents can work around these.

    Maintenance

    ActivityMaintained
    ResponsivenessSyncing