Skip to main content
Glama
drakonkat

wizzy-mcp-tmdb

discover_movies

Find movies using advanced filters including genre, release date, rating, language, cast, crew, and streaming availability to curate personalized film recommendations.

Instructions

Performs advanced discovery of movies with extensive filtering options. Input: Optional parameters including language (ISO 639-1), region (ISO 3166-1), sort_by, certifications, release dates, genres, keywords, watch providers, vote counts, etc. Output: JSON with paginated results. Purpose: Enable complex, criteria-based movie discovery for AI-driven content curation.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
certificationNoFilter by certification (e.g., PG-13)
certification.gteNoCertification greater than or equal to
certification.lteNoCertification less than or equal to
certification_countryNoCertification country (ISO 3166-1)
include_adultNoInclude adult titles (default false)
include_videoNoInclude items with videos
languageNoISO 639-1 language (e.g., en-US)
pageNoPage number (1-500)
primary_release_date.gteNoPrimary release date from (YYYY-MM-DD)
primary_release_date.lteNoPrimary release date to (YYYY-MM-DD)
primary_release_yearNoPrimary release year
regionNoISO 3166-1 region (e.g., US)
release_date.gteNoRelease date from (YYYY-MM-DD)
release_date.lteNoRelease date to (YYYY-MM-DD)
screened_theatricallyNoFilter for movies screened theatrically
sort_byNoSort by (e.g., popularity.desc, release_date.desc, vote_average.desc, primary_release_date.desc, revenue.desc, original_title.asc)
vote_average.gteNoMinimum vote average (0-10)
vote_average.lteNoMaximum vote average (0-10)
vote_count.gteNoMinimum vote count
vote_count.lteNoMaximum vote count
watch_regionNoISO 3166-1 region for watch providers
with_castNoComma-separated person IDs
with_companiesNoComma-separated company IDs
with_crewNoComma-separated person IDs
with_genresNoComma-separated genre IDs
with_keywordsNoComma-separated keyword IDs
with_original_languageNoOriginal language (ISO 639-1)
with_peopleNoComma-separated person IDs
with_release_typeNoComma-separated release types (e.g., 2|3). TMDB expects bitmask but pipe is accepted by API
with_release_type.gteNoMin release type mask (advanced)
with_release_type.lteNoMax release type mask (advanced)
with_runtime.gteNoRuntime min (minutes)
with_runtime.lteNoRuntime max (minutes)
with_statusNoComma-separated status (Rumored|Planned|In Production|Post Production|Released|Canceled)
with_typeNoComma-separated movie types (Documentary, etc.)
with_watch_monetization_typesNoComma-separated monetization types (flatrate|free|ads|rent|buy)
with_watch_providersNoComma-separated watch provider IDs
without_companiesNoComma-separated company IDs to exclude
without_genresNoComma-separated genre IDs to exclude
without_keywordsNoComma-separated keyword IDs to exclude
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions paginated JSON output and that parameters are optional, but fails to disclose critical traits like rate limits, authentication requirements, error handling, or whether this is a read-only operation. For a tool with 40 parameters and no annotations, this is a significant gap.

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 appropriately sized with three sentences that efficiently cover purpose, input/output, and use case. It's front-loaded with the core functionality and avoids unnecessary repetition, though the parameter listing in the middle could be slightly more integrated.

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

Completeness3/5

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

Given the high parameter count (40), no annotations, and no output schema, the description provides basic completeness about the tool's purpose and output format. However, it lacks sufficient behavioral context for safe and effective use, leaving gaps in understanding operational constraints and error scenarios.

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

Parameters3/5

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

Schema description coverage is 100%, so the schema already documents all 40 parameters thoroughly. The description lists some example parameters but doesn't add meaningful semantic context beyond what's in the schema. The baseline score of 3 reflects adequate coverage through the schema alone.

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

Purpose4/5

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

The description clearly states the tool performs 'advanced discovery of movies with extensive filtering options' and specifies it's for 'AI-driven content curation.' It distinguishes from simpler search tools but doesn't explicitly differentiate from sibling tools like 'discover_tv' or 'search_tmdb_movies' beyond the 'movies' focus.

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

Usage Guidelines2/5

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

No explicit guidance on when to use this tool versus alternatives like 'search_tmdb_movies' or 'trending_movies' is provided. The description mentions 'complex, criteria-based movie discovery' which implies usage for detailed filtering, but lacks specific when/when-not scenarios or prerequisite conditions.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/drakonkat/wizzy-mcp-tmdb'

If you have feedback or need assistance with the MCP directory API, please join our Discord server