What's the difference between searching by title vs. using an IMDb ID?

Using an IMDb ID (e.g., `tt0468569`) is the most accurate method because IDs are unique — there's never ambiguity between different films with the same name. Searching by title can return errors if multiple films share the same title (e.g., "King Kong" has multiple versions). If you know the IMDb ID from a link or another source, always prefer `get_by_imdb_id`. Use `get_by_title` when you only know the film name.

Can I get ratings from multiple sources (IMDb, Rotten Tomatoes, Metacritic) at once?

Yes! Use the `get_ratings` tool with either a movie title or IMDb ID. It returns all available ratings from IMDb (out of 10), Rotten Tomatoes (percentage), and Metacritic (out of 100) in a single call. Not all titles have all three ratings — newer or less popular films may only have IMDb data. The tool also returns the IMDb vote count and Metascore as separate fields.

Can I look up details for multiple movies at the same time?

Yes! Use the `get_multiple_by_id` tool with comma-separated IMDb IDs (e.g., `tt0468569,tt1375666,tt0816692` for the Dark Knight trilogy). It fetches details for each ID and returns them combined in one response. If any ID fails, it shows an error for that specific ID while still returning results for the others. This is ideal for franchise comparisons or batch analysis.

What's the difference between short and full plot summaries?

The short plot provides a concise 1-2 paragraph summary — ideal for quick identification or brief descriptions. The full plot offers a much more detailed synopsis with deeper plot points, character arcs, and story resolution. Use short for quick lookups (`get_by_title`, `get_short_plot`) and full when users want comprehensive understanding (`get_full_by_title`, `get_full_by_imdb_id`).

OMDb API MCP Server for Pydantic AI 12 tools — connect in under 2 minutes

Name: OMDb API
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 12 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect OMDb API through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

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Vinkius supports streamable HTTP and SSE.

python

import asyncio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerHTTP

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    server = MCPServerHTTP(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")

    agent = Agent(
        model="openai:gpt-4o",
        mcp_servers=[server],
        system_prompt=(
            "You are an assistant with access to OMDb API "
            "(12 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in OMDb API?"
    )
    print(result.data)

asyncio.run(main())

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* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About OMDb API MCP Server

Connect the OMDb API (Open Movie Database) to any AI agent and access comprehensive movie and TV show data including IMDb ratings, Rotten Tomatoes scores, full cast & crew, plot summaries, box office figures, and awards through natural conversation.

Pydantic AI validates every OMDb API tool response against typed schemas, catching data inconsistencies at build time. Connect 12 tools through Vinkius and switch between OpenAI, Anthropic, or Gemini without changing your integration code. full type safety, structured output guarantees, and dependency injection for testable agents.

What you can do

Search Movies & Series — Find any movie or TV show by title keyword with results showing IMDb ID, type, year, and poster references
Get by IMDb ID — Retrieve complete details for any title using its unique IMDb ID (most accurate method, no title ambiguity)
Get by Title — Look up any movie or series by its exact title with optional filters for type and release year
Full Plot Synopses — Access both short and full-length plot summaries for deep understanding of any film or series
Multi-Source Ratings — Get ratings from IMDb, Rotten Tomatoes, and Metacritic all in one call to compare critical consensus
Search by Type — Filter searches specifically for movies, TV series, or episodes to narrow results precisely
Episode Details — Get information about specific TV episodes including air date, synopsis, director, and writer
Batch Lookup — Retrieve details for multiple titles at once using comma-separated IMDb IDs — perfect for franchise comparisons
Box Office Data — Access theatrical box office gross figures for movies
Production & Awards — Get studio information, award details, and content ratings (PG, PG-13, R, etc.)

The OMDb API MCP Server exposes 12 tools through the Vinkius. Connect it to Pydantic AI 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 OMDb API to Pydantic AI via MCP

Follow these steps to integrate the OMDb API MCP Server with Pydantic AI.

Install Pydantic AI

Run pip install pydantic-ai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save to agent.py and run: python agent.py

Explore tools

The agent discovers 12 tools from OMDb API with type-safe schemas

Why Use Pydantic AI with the OMDb API MCP Server

Pydantic AI provides unique advantages when paired with OMDb API through the Model Context Protocol.

Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application

Model-agnostic architecture. switch between OpenAI, Anthropic, or Gemini without changing your OMDb API integration code

Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors

Dependency injection system cleanly separates your OMDb API connection logic from agent behavior for testable, maintainable code

OMDb API + Pydantic AI Use Cases

Practical scenarios where Pydantic AI combined with the OMDb API MCP Server delivers measurable value.

Type-safe data pipelines: query OMDb API with guaranteed response schemas, feeding validated data into downstream processing

API orchestration: chain multiple OMDb API tool calls with Pydantic validation at each step to ensure data integrity end-to-end

Production monitoring: build validated alert agents that query OMDb API and output structured, schema-compliant notifications

Testing and QA: use Pydantic AI's dependency injection to mock OMDb API responses and write comprehensive agent tests

OMDb API MCP Tools for Pydantic AI (12)

These 12 tools become available when you connect OMDb API to Pydantic AI via MCP:

get_by_imdb_id

g., "tt0468569" for The Dark Knight). Returns: Title, Year, Rated (content rating), Released (date), Runtime, Genre, Director, Writer, Actors, Plot, Language, Country, Awards, Ratings (IMDb, Rotten Tomatoes, Metacritic), Metascore, imdbRating, imdbVotes, imdbID, Type (movie/series/episode), DVD release date, BoxOffice gross, Production studio, and Website. Use this when you have an IMDb ID and need complete movie/series information. This is the most accurate method — IMDb IDs are unique and unambiguous. Optional plot parameter: "short" (brief synopsis) or "full" (complete plot summary). Get complete details for a movie or TV series using its IMDb ID

get_by_title

Returns the same fields as get_by_imdb_id: Title, Year, Rated, Runtime, Genre, Director, Writer, Actors, Plot, Ratings (IMDb, Rotten Tomatoes, Metacritic), BoxOffice, Production studio, etc. Use this when you know the title but not the IMDb ID. IMPORTANT: If multiple items share the same title, the API may return the first match or an error. To narrow results, use the optional type filter (movie/series/episode) and year filter. For more precise matching, prefer get_by_imdb_id when available. Get details for a movie or TV series by its exact title

get_episode

Returns: Title (episode name), Year (air year), Released (air date), Runtime, Genre, Director, Writer, Actors, Plot (episode synopsis), Language, Country, Ratings, imdbRating, imdbVotes, imdbID, and Type (episode). Use this after finding an episode via search_episodes to get its full details. The IMDb ID is required — get it from search results or from a TV series season/episode listing. Get details for a specific TV episode using its IMDb ID

get_full_by_imdb_id

This is the same as get_by_imdb_id but always uses plot="full" for the most comprehensive synopsis. Returns: Title, Year, Rated, Released, Runtime, Genre, Director, Writer, Actors, full Plot, Language, Country, Awards, Ratings (IMDb, Rotten Tomatoes, Metacritic), Metascore, imdbRating, imdbVotes, imdbID, Type, DVD release date, BoxOffice gross, Production studio, and Website. Using IMDb ID is the most accurate method — IDs are unique and unambiguous unlike titles which can have duplicates. The full plot provides deeper synopsis detail compared to the short version. Get the most detailed information for a movie or series using its IMDb ID

get_full_by_title

This is the same as get_by_title but always uses plot="full" for the most comprehensive synopsis. Returns: Title, Year, Rated, Released, Runtime, Genre, Director, Writer, Actors, full Plot, Language, Country, Awards, Ratings (IMDb, Rotten Tomatoes, Metacritic), Metascore, imdbRating, imdbVotes, imdbID, Type, DVD release date, BoxOffice gross, Production studio, and Website. Use this when users want the complete plot summary and all metadata for a specific title. The full plot can be significantly longer than the short version, providing deeper synopsis detail. Get the most detailed information for a movie or series by title

get_multiple_by_id

Each ID is fetched individually and results are combined into one response. If any ID fails, it will be returned with an error message while others still succeed. Use this when comparing multiple films, getting info for a franchise, or batch-processing a list of IMDb IDs. Format: comma-separated IMDb IDs without spaces (e.g., "tt0468569,tt1375666,tt0816692"). Each result includes: Title, Year, Rated, Runtime, Genre, Director, Actors, Plot (short), Ratings, imdbRating, imdbVotes, Type, BoxOffice, Production, and more. Get details for multiple movies/series at once using their IMDb IDs

get_ratings

Also returns: Title, Year, Type, imdbRating, imdbVotes, and Metascore as individual fields. Use this when users ask "what is the rating of...", "how is X rated?", or want to compare scores across platforms. You can search by title (first parameter) or by IMDb ID (set use_imdb_id=true for the second parameter). Note: Not all titles have ratings from all three sources — some may be missing. Get all available ratings (IMDb, Rotten Tomatoes, Metacritic) for a movie or series

get_short_plot

The short plot provides a concise synopsis — ideal for quick identification or brief descriptions. Returns: Title, Year, Rated, Runtime, Genre, Director, Actors, short Plot, Ratings, and other metadata. Use this when users want a quick summary without the lengthy full plot. For the complete synopsis, use get_full_by_title or get_full_by_imdb_id instead. Get a brief plot summary for a movie or series by title

search

Returns a paginated list of matching titles. Each result includes: Title, Year, IMDb ID, Type (movie/series/episode), and Poster URL. Results are paginated (10 per page); use the page parameter to get more results (pages 1-100). Use this when users ask to "find movies about..." or "search for..." a topic. Optional filters: type (movie/series/episode) and year (YYYY format). Note: Search results are brief — use get_by_imdb_id or get_by_title with the returned IMDb ID for full details. Search for movies, TV series, or episodes by title keyword

search_episodes

Returns a paginated list of matching episode titles. Each result includes: Title, Year, IMDb ID, Type (always "episode"), and Poster URL. Use this when users want to find specific TV episodes by title or keyword. Episode titles often include the series name followed by the episode name. Results are paginated (10 per page); use the page parameter to navigate results. Search for TV episodes only (excludes movies and full series)

search_movies

Returns a paginated list of matching movie titles. Each result includes: Title, Year, IMDb ID, Type (always "movie"), and Poster URL. Use this when users specifically want to find movies (not TV shows) by keyword. Results are paginated (10 per page); use the page parameter to navigate results. Optional year filter narrows results to a specific release year. Search for movies only (excludes TV series and episodes)

search_series

Returns a paginated list of matching series titles. Each result includes: Title, Year (or year range like "2008-2013"), IMDb ID, Type (always "series"), and Poster URL. Use this when users specifically want to find TV shows (not movies) by keyword. Results are paginated (10 per page); use the page parameter to navigate results. Optional year filter narrows results to series that started in a specific year. Search for TV series only (excludes movies and episodes)

Example Prompts for OMDb API in Pydantic AI

Ready-to-use prompts you can give your Pydantic AI agent to start working with OMDb API immediately.

"What are the ratings for The Dark Knight?"

"Search for movies directed by Christopher Nolan with Interstellar in the title."

"Compare the Lord of the Rings trilogy movies: tt0120737, tt0167261, tt0167260"

Troubleshooting OMDb API MCP Server with Pydantic AI

Common issues when connecting OMDb API to Pydantic AI through the Vinkius, and how to resolve them.

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

OMDb API + Pydantic AI FAQ

Common questions about integrating OMDb API MCP Server with Pydantic AI.

How does Pydantic AI discover MCP tools?

Create an MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.

Does Pydantic AI validate MCP tool responses?

Yes. When you define result types as Pydantic models, every tool response is validated against the schema. Invalid data raises a clear error instead of silently corrupting your pipeline.

Can I switch LLM providers without changing MCP code?

Absolutely. Pydantic AI abstracts the model layer. your OMDb API MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.