OMDb API MCP Server for LlamaIndex 12 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add OMDb API as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
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import asyncio
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
mcp_client = BasicMCPClient("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
mcp_tool_spec = McpToolSpec(client=mcp_client)
tools = await mcp_tool_spec.to_tool_list_async()
agent = FunctionAgent(
tools=tools,
llm=OpenAI(model="gpt-4o"),
system_prompt=(
"You are an assistant with access to OMDb API. "
"You have 12 tools available."
),
)
response = await agent.run(
"What tools are available in OMDb API?"
)
print(response)
asyncio.run(main())
* 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.
LlamaIndex agents combine OMDb API tool responses with indexed documents for comprehensive, grounded answers. Connect 12 tools through Vinkius and query live data alongside vector stores and SQL databases in a single turn. ideal for hybrid search, data enrichment, and analytical workflows.
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 LlamaIndex 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 LlamaIndex via MCP
Follow these steps to integrate the OMDb API MCP Server with LlamaIndex.
Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai
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
Why Use LlamaIndex with the OMDb API MCP Server
LlamaIndex provides unique advantages when paired with OMDb API through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine OMDb API tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain OMDb API tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query OMDb API, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what OMDb API tools were called, what data was returned, and how it influenced the final answer
OMDb API + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the OMDb API MCP Server delivers measurable value.
Hybrid search: combine OMDb API real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query OMDb API to augment indexed data with live information before generating user-facing responses
Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying OMDb API for fresh data
Analytical workflows: chain OMDb API queries with LlamaIndex's data connectors to build multi-source analytical reports
OMDb API MCP Tools for LlamaIndex (12)
These 12 tools become available when you connect OMDb API to LlamaIndex 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 LlamaIndex
Ready-to-use prompts you can give your LlamaIndex 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 LlamaIndex
Common issues when connecting OMDb API to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpOMDb API + LlamaIndex FAQ
Common questions about integrating OMDb API MCP Server with LlamaIndex.
How does LlamaIndex connect to MCP servers?
Can I combine MCP tools with vector stores?
Does LlamaIndex support async MCP calls?
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Connect OMDb API to LlamaIndex
Get your token, paste the configuration, and start using 12 tools in under 2 minutes. No API key management needed.