OTT Helper MCP Server
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Alternatives to OTT Helper MCP Server
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Related Servers
- FlicenseAqualityCmaintenanceEnables searching for movies and TV shows and retrieving streaming availability data across multiple platforms and countries.32-
- FlicenseNot gradedqualityDmaintenanceTracks movies, books, and TV shows with ratings and preferences, providing intelligent cross-media recommendations. Automatically fetches metadata from OMDB, Google Books, and TMDB to help manage watchlists and analyze viewing patterns.1-
- FlicenseBqualityDmaintenanceProvides Indian movie recommendations within Claude Desktop, allowing users to filter by genre, language, rating, and year, search for specific films, or discover random recommendations from Bollywood and regional cinema.3-
- AlicenseNot gradedqualityDmaintenanceIntegrates with The Movie Database (TMDB) API to provide movie information, search capabilities, and recommendations.6 npmMIT
- AlicenseNot gradedqualityCmaintenanceIntegrates with The Movie Database (TMDB) API to provide movie information, search capabilities, and recommendations.8 npm76MIT
- AlicenseBqualityCmaintenanceEnables movie and TV recommendation workflows, including title resolution, evidence tracking, candidate retrieval from MovieLens and TMDB, and recording of recommendation runs and reactions.8MIT
TDQS
Scored across 8 tools
Several tools overlap in functionality: get_recommendations_by_platform_and_rating and get_recommendations_by_genre_and_rating are subsets of get_recommendations_by_criteria, and get_top_rated_content may duplicate recommendation results. This could confuse an agent when choosing the appropriate tool.
Most tools follow a 'get_' prefix pattern, but 'search_content_by_title' uses 'search_' instead. The filter-based names are clear and consistent, with only minor deviations from the dominant convention.
Eight tools provide a focused yet comprehensive set for an OTT helper, avoiding both excessive granularity and insufficient coverage. The number is well balanced for the domain.
The toolset covers search, recommendations, filtering, content details, top-rated items, and available filters. Missing features like user watchlists or reviews are not essential for the stated purpose, so the surface is reasonably complete.