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TMDB MCP Server

MCP Server

Your gateway to movie data and recommendations

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Updated Dec 25, 2024

About

The TMDB MCP Server connects to The Movie Database API, offering tools for searching movies, fetching trending titles, and getting personalized recommendations. It exposes movie resources in JSON format for easy integration with AI applications.

Capabilities

Resources
Access data sources
Tools
Execute functions
Prompts
Pre-built templates
Sampling
AI model interactions

mcp-server-tmdb MCP server

The TMDB MCP Server bridges Claude and other AI assistants with The Movie Database (TMDB), a comprehensive, community‑curated repository of film and television metadata. By exposing TMDB’s rich API through a standardized MCP interface, the server eliminates the need for developers to write custom wrappers or manage authentication flows. Instead, a single configuration entry in an AI client’s server list unlocks instant access to search, recommendation, and trending data.

At its core, the server offers three intuitive tools: search_movies, get_recommendations, and get_trending. Each tool accepts a concise set of parameters (e.g., a keyword string or a numeric movie ID) and returns structured JSON payloads that include titles, release dates, ratings, overviews, genres, and key cast members. The search_movies tool is ideal for quick queries such as “movies about space exploration,” while get_recommendations lets an assistant surface a curated list of films similar to a user‑selected title. The get_trending tool pulls the top ten movies for today or this week, enabling chat flows that keep users updated on current releases.

Beyond tools, the server exposes a Movies resource () that delivers an exhaustive snapshot of any film. This includes director names, a truncated cast list, selected reviews, and poster URLs—all formatted as JSON. Developers can embed these resources directly into dialogue prompts or chain them with other MCP tools to build sophisticated cinematic assistants.

Real‑world scenarios abound: a streaming recommendation bot can query trending titles and surface personalized suggestions; a trivia game can fetch quick facts about a user’s favorite actors; or an itinerary planner might pull in movie schedules for a travel destination. Because the server handles API key management and rate limiting internally, AI developers can focus on crafting conversational flows rather than infrastructure concerns.

In summary, the TMDB MCP Server transforms raw movie data into a developer‑friendly API layer, enabling AI assistants to deliver instant, accurate film information and recommendations with minimal effort.