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Grinv

TMDB MCP Server

Get compact movie card(s)

get_movies
Read-only

Retrieve compact movie cards with title, year, genres, and vote average for up to 20 TMDB IDs in a single call. Optionally includes ratings from IMDb, Rotten Tomatoes, and Metacritic.

Instructions

Get a compact card — title, year, genres, vote average, and (opt-in) ratings — for 1-20 movies by TMDB id in one call. Deliberately trimmed (no overview, cast, budget, certifications, production companies, etc.): use this for a single id too when you only need that headline info and not the full get_movie payload, not just for checking many at once. Call get_movie instead when you need the full details for a title (including region-specific certification). A bad/unknown id never fails the whole call — that entry comes back {id, found:false, reason} instead, in the same order as ids.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idsYesTMDB movie ids to fetch (1-20). Get them from search_movies/discover_movies/get_similar/get_movie_recommendations/etc.
languageNoOverride the response language (ISO-639-1, optionally with a region), e.g. 'ru-RU' or 'en-US'. Localizes titles/overviews/genre names. Defaults to the server's TMDB_LANGUAGE.
include_ratingsNoIf true, enrich every card with compact IMDb/Rotten Tomatoes/Metacritic ratings from OMDb (requires OMDB_API_KEY) — one extra OMDb lookup per id, so a large batch means a burst of OMDb calls; mind OMDb's own rate limit. Unlike get_movie/get_tv, defaults to false (off) here.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultsYes
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Discloses that bad IDs do not fail the call, returning {id, found:false, reason} in order. Mentions OMDb rate limits for include_ratings. Annotations already declare readOnlyHint and openWorldHint; description adds complementary behavioral context without contradiction.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Well-structured and front-loaded with purpose, but slightly verbose in the middle listing exclusions and use cases. Each sentence earns its place, though could tighten some phrasing.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given 3 parameters, output schema present, and annotations, the description is complete. Covers error behavior, rate limits, scope of data, and contrasts with sibling tool. No gaps.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, but description adds meaningful context: IDs sourced from search/discover/etc., language override localization, include_ratings defaults to false and explains OMDb burst calls. Provides value beyond schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it fetches compact movie cards for 1-20 TMDB IDs, explicitly listing included fields (title, year, genres, vote average, ratings) and contrasting with get_movie for full details. It distinguishes from siblings effectively.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides explicit when-to-use (single or multiple IDs for headline info) and when-not-to-use (call get_movie for full details including region-specific certification). Also explains handling of bad IDs.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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