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The Movie Database (TMDb) MCP Server for OpenAI Agents SDK 15 tools — connect in under 2 minutes

Built by Vinkius GDPR 15 Tools SDK

The OpenAI Agents SDK enables production-grade agent workflows in Python. Connect The Movie Database (TMDb) through the Vinkius and your agents gain typed, auto-discovered tools with built-in guardrails — no manual schema definitions required.

Vinkius supports streamable HTTP and SSE.

python
import asyncio
from agents import Agent, Runner
from agents.mcp import MCPServerStreamableHttp

async def main():
    # Your Vinkius token — get it at cloud.vinkius.com
    async with MCPServerStreamableHttp(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ) as mcp_server:

        agent = Agent(
            name="The Movie Database (TMDb) Assistant",
            instructions=(
                "You help users interact with The Movie Database (TMDb). "
                "You have access to 15 tools."
            ),
            mcp_servers=[mcp_server],
        )

        result = await Runner.run(
            agent, "List all available tools from The Movie Database (TMDb)"
        )
        print(result.final_output)

asyncio.run(main())
The Movie Database (TMDb)
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About The Movie Database (TMDb) MCP Server

Connect The Movie Database (TMDb) to any AI agent and unlock the world's most comprehensive movie and TV show database through natural conversation. TMDb is the same database used by major streaming platforms, media players, and entertainment apps worldwide.

The OpenAI Agents SDK auto-discovers all 15 tools from The Movie Database (TMDb) through native MCP integration. Build agents with built-in guardrails, tracing, and handoff patterns — chain multiple agents where one queries The Movie Database (TMDb), another analyzes results, and a third generates reports, all orchestrated through the Vinkius.

What you can do

  • Movie Search — Search any movie by title, keyword, or phrase with release dates, ratings, overviews, and poster images
  • TV Show Search — Find TV shows and series with season counts, episode information, network details, and air dates
  • Unified Multi-Search — Search movies, TV shows, and people simultaneously for broad entertainment queries
  • Complete Movie Details — Get full movie metadata including budget, revenue, runtime, genres, production studios, taglines, and IMDb cross-references
  • Cast & Crew Information — Retrieve complete cast lists with actor characters and crew details (directors, writers, producers, cinematographers)
  • Trailers & Videos — Access official trailers, teasers, behind-the-scenes clips, and promotional videos (YouTube links)
  • Popular & Top Rated — Browse currently popular movies/TV shows and all-time highest-rated content
  • Trending Content — See what is trending today or this week across movies, TV shows, and people
  • Advanced Movie Discovery — Filter movies by genre, year, minimum rating, production studio (e.g., Warner Bros., Marvel), and sort by popularity, rating, or revenue
  • Movie Recommendations — Get similar movie suggestions based on a specific film using TMDb's recommendation algorithm
  • Person Profiles — Search for actors, directors, and crew with biographies, filmographies, and combined credits
  • External ID Lookup — Convert IMDb IDs (tt0111161), TVDb IDs, and other external identifiers to TMDb entries
  • Genre Reference — Access the complete genre database with IDs for advanced filtering

The The Movie Database (TMDb) MCP Server exposes 15 tools through the Vinkius. Connect it to OpenAI Agents SDK in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect The Movie Database (TMDb) to OpenAI Agents SDK via MCP

Follow these steps to integrate the The Movie Database (TMDb) MCP Server with OpenAI Agents SDK.

01

Install the SDK

Run pip install openai-agents in your Python environment

02

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com

03

Run the script

Save the code above and run it: python agent.py

04

Explore tools

The agent will automatically discover 15 tools from The Movie Database (TMDb)

Why Use OpenAI Agents SDK with the The Movie Database (TMDb) MCP Server

OpenAI Agents SDK provides unique advantages when paired with The Movie Database (TMDb) through the Model Context Protocol.

01

Native MCP integration via `MCPServerSse` — pass the URL and the SDK auto-discovers all tools with full type safety

02

Built-in guardrails, tracing, and handoff patterns let you build production-grade agents without reinventing safety infrastructure

03

Lightweight and composable: chain multiple agents and MCP servers in a single pipeline with minimal boilerplate

04

First-party OpenAI support ensures optimal compatibility with GPT models for tool calling and structured output

The Movie Database (TMDb) + OpenAI Agents SDK Use Cases

Practical scenarios where OpenAI Agents SDK combined with the The Movie Database (TMDb) MCP Server delivers measurable value.

01

Automated workflows: build agents that query The Movie Database (TMDb), process the data, and trigger follow-up actions autonomously

02

Multi-agent orchestration: create specialist agents — one queries The Movie Database (TMDb), another analyzes results, a third generates reports

03

Data enrichment pipelines: stream data through The Movie Database (TMDb) tools and transform it with OpenAI models in a single async loop

04

Customer support bots: agents query The Movie Database (TMDb) to resolve tickets, look up records, and update statuses without human intervention

The Movie Database (TMDb) MCP Tools for OpenAI Agents SDK (15)

These 15 tools become available when you connect The Movie Database (TMDb) to OpenAI Agents SDK via MCP:

01

discover_movies

Find movies matching very specific criteria. Available filters: genre (genre IDs, comma-separated for OR), year, sortBy (popularity, rating, revenue, release date), vote_average.gte (minimum rating), with_companies (studio IDs, comma-separated), with_keywords (keyword IDs), primary_release_date.gte/lte (date range YYYY-MM-DD). Sort options: popularity.desc, popularity.asc, release_date.desc, release_date.asc, vote_average.desc, vote_average.asc, revenue.desc, revenue.asc, title.asc, title.desc. Use this for complex queries like "action movies from 2024 with rating above 7", "Warner Bros movies from the last year", or "horror movies sorted by rating". Genre IDs can be obtained from the get_genres tool. Company ID 17 = Warner Bros, 420 = Marvel Studios, 33 = Universal, etc. Discover movies with advanced filtering by genre, year, rating, studio, and more

02

find_by_external_id

The externalSource parameter must be one of: "imdb_id", "tvdb_id", "freebase_mid", "freebase_id", "tvrage_id", "wikidata_id". Returns matching movies, TV shows, and/or people from TMDb that have this external ID. Use this when you have an IMDb ID (like "tt0111161" for Shawshank Redemption) and want to find the corresponding TMDb entry. Common use case: converting IMDb IDs to TMDb IDs for use with other tools. IMDb IDs for movies start with "tt" followed by numbers (e.g., "tt0137523" for Fight Club). Results include all matching items across movies, TV, and people categories. Find movies, TV shows, or people using external IDs (IMDb, TVDb, etc)

03

get_genres

Each genre includes: id (numeric ID used for filtering in other tools) and name (localized genre name). Use this to get genre IDs needed for the discover_movies tool or to answer questions about available genres. Common movie genres: 28=Action, 12=Adventure, 16=Animation, 35=Comedy, 80=Crime, 18=Drama, 14=Fantasy, 27=Horror, 878=Science Fiction, 53=Thriller, 10749=Romance. The type parameter must be "movie" or "tv". Optional language parameter returns localized genre names. Get the complete list of movie or TV show genres with their IDs

04

get_movie

Returns: title, overview, runtime, release date, budget, revenue, vote average, vote count, genres, production companies, production countries, spoken languages, status, tagline, homepage, IMDb ID, poster/backdrop image paths, and collection information (if part of a franchise). Use this after a search to get full details about a specific movie. The movieId parameter is the TMDb ID (integer) returned by search_movies or other movie list tools. Optional language parameter returns localized title and overview if available. Get complete details for a specific movie by its TMDb ID

05

get_movie_credits

Returns two arrays: "cast" (actors with their characters, order, and profile images) and "crew" (directors, producers, writers, cinematographers, editors, composers, etc. with their jobs and departments). Use this when users ask "who starred in...", "who directed...", or want the full cast list of a movie. The movieId is the TMDb ID from search results. Cast includes: actor name, character name, order (billing order), profile image path. Crew includes: name, job title (Director, Producer, Screenplay, etc.), department. Get complete cast and crew information for a specific movie

06

get_movie_recommendations

TMDb uses an algorithm that considers genre, keywords, cast, crew, and user rating patterns to suggest similar movies that fans of the original might enjoy. Each recommendation includes: title, release date, overview, poster path, vote average, vote count, and TMDb ID. Use this when users ask "if I liked X, what should I watch?", "movies similar to...", or "recommendations for...". The movieId is the TMDb ID of the reference movie. Results are paginated; use the page parameter to get more recommendations. Get movie recommendations based on a specific movie (similar titles)

07

get_movie_videos

Each video result includes: video key (YouTube ID), site (YouTube), type (Trailer, Teaser, Clip, Behind the Scenes, etc.), name, size (resolution), official status, and publish date. Use this when users want to watch trailers, find official promotional videos, or access movie video content. YouTube videos can be viewed at: https://www.youtube.com/watch?v={key}. The movieId is the TMDb movie ID. Get trailers, teasers, clips, and behind-the-scenes videos for a movie

08

popular_movies

Each movie includes: title, release date, overview, poster path, vote average, vote count, genre IDs, and TMDb ID. Use this when users ask "what movies are popular now?", "what is trending?", or want movie recommendations. Results are updated regularly based on TMDb user activity. Optional: page for pagination, region (ISO 3166-1 country code like "US", "BR") for country-specific popularity, and language for localized titles and descriptions. Get a list of currently popular movies on TMDb

09

popular_tv

Popularity is based on user activity, view counts, and trending data. Each TV show includes: name, first air date, overview, poster path, vote average, vote count, genre IDs, number of seasons, number of episodes, origin country, and TMDb ID. Use this when users ask "what TV shows are popular?", "what should I watch?", or want series recommendations. Optional: page for pagination and language for localized titles and descriptions. Get a list of currently popular TV shows on TMDb

10

search_movies

Returns movie titles, release dates, overview descriptions, poster images, vote averages, and TMDb IDs. Use this when users ask to find movies by title, search for films about a topic, or look up movies from a specific year. The query parameter is required and should be the movie title or search term. Optional parameters: year (YYYY format) to filter by release year, page for pagination (1-500), and language (ISO 639-1 code like "pt-BR", "en-US", "es") to get results in a specific language. Example: query="The Matrix", year="1999" returns the 1999 sci-fi classic. Search for movies by title, keyword, or phrase in the TMDb database

11

search_multi

Returns results from all three categories with a media_type field indicating the type ("movie", "tv", or "person"). Use this when users provide a general search term and you want to return all relevant results across content types. Ideal for broad queries like "Christopher Nolan" (returns movies directed by him + person profile) or "Star Wars" (returns movies + TV series). The query parameter is required. Optional: page for pagination and language for localized results. Search movies, TV shows, and people simultaneously in the TMDb database

12

search_tv

Returns TV show names, first air dates, episode counts, overview descriptions, poster images, vote averages, and TMDb IDs. Use this when users ask to find TV series, look up shows by title, or search for programs about a specific topic. The query parameter is required. Optional: year to filter by first air date year, page for pagination, and language for localized results. Example: query="Breaking Bad" returns the critically acclaimed drama series. Search for TV shows by title or keyword in the TMDb database

13

top_rated_movies

These are the critically acclaimed films with the best user ratings. Each movie includes: title, release date, overview, vote average, vote count, poster path, genre IDs, and TMDb ID. Use this when users ask for "best movies ever", "top rated films", "highest rated movies", or want quality recommendations. This list includes classics like The Shawshank Redemption, The Godfather, and other critically acclaimed films. Optional: page for pagination and language for localized results. Get a list of the highest-rated movies of all time on TMDb

14

top_rated_tv

These are the most critically acclaimed series with the best user ratings. Each TV show includes: name, first air date, overview, vote average, vote count, poster path, number of seasons and episodes, and TMDb ID. Use this when users ask for "best TV shows ever", "top rated series", or want quality TV recommendations. This list includes acclaimed series like Breaking Bad, Band of Brothers, Chernobyl, and other top-rated shows. Optional: page for pagination and language for localized results. Get a list of the highest-rated TV shows of all time on TMDb

15

trending

The mediaType parameter can be: "movie", "tv", "person", or "all" (returns mixed results with media_type field). The timeWindow parameter can be: "day" (trending today) or "week" (trending this week). Each result includes: title/name, overview, poster path, vote average, popularity score, and media type. Use this when users ask "what is trending?", "what is popular today?", or want to see what is currently hot in entertainment. The trending algorithm considers user activity, page views, and search patterns on TMDb. Get trending content (movies, TV shows, or people) on TMDb for today or this week

Example Prompts for The Movie Database (TMDb) in OpenAI Agents SDK

Ready-to-use prompts you can give your OpenAI Agents SDK agent to start working with The Movie Database (TMDb) immediately.

01

"What movies are trending today?"

02

"Search for movies directed by Christopher Nolan with rating above 8."

03

"Who starred in The Matrix and what other movies have they been in?"

Troubleshooting The Movie Database (TMDb) MCP Server with OpenAI Agents SDK

Common issues when connecting The Movie Database (TMDb) to OpenAI Agents SDK through the Vinkius, and how to resolve them.

01

MCPServerStreamableHttp not found

Ensure you have the latest version: pip install --upgrade openai-agents
02

Agent not calling tools

Make sure your prompt explicitly references the task the tools can help with.

The Movie Database (TMDb) + OpenAI Agents SDK FAQ

Common questions about integrating The Movie Database (TMDb) MCP Server with OpenAI Agents SDK.

01

How does the OpenAI Agents SDK connect to MCP?

Use MCPServerSse(url=...) to create a server connection. The SDK auto-discovers all tools and makes them available to your agent with full type information.
02

Can I use multiple MCP servers in one agent?

Yes. Pass a list of MCPServerSse instances to the agent constructor. The agent can use tools from all connected servers within a single run.
03

Does the SDK support streaming responses?

Yes. The SDK supports SSE and Streamable HTTP transports, both of which work natively with the Vinkius.

Connect The Movie Database (TMDb) to OpenAI Agents SDK

Get your token, paste the configuration, and start using 15 tools in under 2 minutes. No API key management needed.