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simentob

TMDB MCP Server

by simentob

tmdb_multi_search

Find movies, TV shows, and people in a single query. Uses TMDB API to return combined results for all content types.

Instructions

Multi-search for movies, TV shows, and people using the TMDB API.
Args:
    query: The text query to search for (required).
    include_adult: Whether to include adult content (default: False).
    language: Language code (default: en-US).
    page: Page of results (default: 1).
Returns:
    Formatted string with multi-search results.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageNo
queryYes
languageNoen-US
include_adultNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

With no annotations, the description carries the full burden. It discloses the return type ('Formatted string with multi-search results') and lists parameters, but adds little beyond the schema. It does not mention rate limits, authentication, pagination behavior, or how results are grouped, though for a simple search tool this may be sufficient.

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?

The description is efficiently structured with an overview line, Args section, and Returns section. Every sentence is informative and there is no redundant fluff, though the format could be tighter.

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

Completeness4/5

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

Given the tool's simplicity and the presence of an output schema, the description covers the core aspects: purpose, parameters, and return type. It does not explicitly explain how multi-search results are organized, but that is likely handled by the output schema, so this is acceptable.

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

Parameters4/5

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

Schema description coverage is 0%, so the description must compensate. It lists all four parameters with meaningful explanations ('text query to search for', 'include adult content', 'Language code', 'Page of results') and includes defaults. This adds clarity beyond the bare schema names.

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 'Multi-search for movies, TV shows, and people using the TMDB API', which specifies the verb (search), the resource (TMDB API), and the scope (multiple types). This distinguishes it from siblings like tmdb_search_movies, which likely focuses on movies only.

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

Usage Guidelines3/5

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

The description implies usage for multi-type searches but does not explicitly state when to use this tool versus alternatives like tmdb_search_movies for movie-only queries. No exclusions or conditions are provided, just the general scope.

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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