TMDB MCP Server
Allows searching for movies and TV shows by title, retrieving detailed metadata (runtime, budget, seasons, etc.), discovering trending content, and searching for people (actors, directors, etc.) via the TMDB API.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@TMDB MCP Serversearch for the movie Inception"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
TMDB MCP Server
A Model Context Protocol (MCP) server that allows LLMs to search for movies and TV shows using the The Movie Database (TMDB) API.
Features
Search Movies: Find movies by title with support for region and language.
Search TV Shows: Find TV shows by title with language support.
Get Details: Retrieve detailed metadata for movies and TV shows (runtime, budget, seasons, etc.).
Trending: Discover today's or this week's trending movies and TV shows.
Search People: Search for actors, directors, and other crew members.
Direct Links: Provides TMDb URLs for easy access to more details.
Related MCP server: wizzy-mcp-tmdb
Prerequisites
Node.js (v18 or higher)
A TMDB API Key. You can get one by creating an account on themoviedb.org and applying for an API key in your account settings.
Configuration
MCP Client Configuration (e.g., Claude Desktop)
To use this server with Claude Desktop, add it to your claude_desktop_config.json:
macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
Windows: %APPDATA%\Claude\claude_desktop_config.json
{
"mcpServers": {
"tmdb": {
"command": "npx",
"args": ["-y", "@lonzzi/tmdb-mcp-server"],
"env": {
"TMDB_API_KEY": "your_api_key_here"
}
}
}
}Available Tools
All tools support an optional language argument (e.g., en-US, zh-CN, fr-FR) to get localized results. Default is en-US.
search_movies
Search for movies on TMDB by title.
Arguments:
query(string, required): The movie title to search for.language(string, optional): Language code (default:en-US).region(string, optional): ISO 3166-1 code to filter release dates (e.g.,US,KR).
search_tv_shows
Search for TV shows on TMDB by title.
Arguments:
query(string, required): The TV show title to search for.language(string, optional): Language code (default:en-US).
get_movie_details
Get detailed information about a specific movie.
Arguments:
movieId(number, required): The TMDB ID of the movie.language(string, optional): Language code (default:en-US).
get_tv_show_details
Get detailed information about a specific TV show.
Arguments:
tvShowId(number, required): The TMDB ID of the TV show.language(string, optional): Language code (default:en-US).
get_trending_movies
Get the daily or weekly trending movies.
Arguments:
timeWindow(string, optional):dayorweek(default:week).language(string, optional): Language code (default:en-US).
get_trending_tv
Get the daily or weekly trending TV shows.
Arguments:
timeWindow(string, optional):dayorweek(default:week).language(string, optional): Language code (default:en-US).
search_person
Search for people (actors, directors, etc.).
Arguments:
query(string, required): The name to search for.language(string, optional): Language code (default:en-US).
Development
Clone the repository:
git clone https://github.com/lonzzi/tmdb-mcp-server.git cd tmdb-mcp-serverInstall dependencies:
npm installCreate a
.envfile with yourTMDB_API_KEY.Build the project:
npm run build
Running Tests
npm testAvailable Tools
7 toolsget_movie_detailsA
Get detailed information about a specific movie by its ID
| Name | Required | Description | Default |
|---|---|---|---|
| movieId | Yes | The ID of the movie | |
| language | No | Language code (e.g. 'en-US', 'zh-CN') |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It only states 'Get detailed information,' which implies a read operation but does not address permissions, side effects, or other behavioral aspects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no wasted words, making it efficient and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (2 params, no output schema), the description is adequate but lacks usage guidance and behavioral context, leaving room for improvement.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds minimal meaning beyond the schema by saying 'by its ID,' but does not elaborate on parameter formats or constraints.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Get detailed information about a specific movie by its ID' uses a specific verb and resource, clearly distinguishing it from sibling tools like get_trending_movies or search_movies.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when you have a movie ID, but provides no explicit guidance on when to use it versus alternative tools or when not to use it, resulting in only implied usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_trending_moviesC
Get a list of trending movies
| Name | Required | Description | Default |
|---|---|---|---|
| language | No | Language code (e.g. 'en-US', 'zh-CN') | |
| timeWindow | No | Time window for trending content (default: week) |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description carries the full burden. It does not disclose any behavioral traits such as read-only or potential side effects. It only states the obvious purpose.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence with no fluff. It is appropriately sized for a simple tool but could be more structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and no annotations, the description is incomplete. It does not explain response format, pagination, or what 'trending' means.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
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 both parameters. The description adds no extra meaning beyond the tool's purpose.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Get a list of trending movies' clearly states the verb and resource. It distinguishes from siblings like get_trending_tv by specifying 'movies', but does not explicitly mention alternatives.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus siblings like get_trending_tv or search_movies. The description lacks any usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_trending_tvB
Get a list of trending TV shows
| Name | Required | Description | Default |
|---|---|---|---|
| language | No | Language code (e.g. 'en-US', 'zh-CN') | |
| timeWindow | No | Time window for trending content (default: week) |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden for behavioral disclosure. It only states 'Get a list' without mentioning side effects, rate limits, authentication, or return structure (e.g., pagination, data model). This is insufficient for a read operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single, front-loaded sentence that efficiently conveys the core purpose. No unnecessary words or repetition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with two optional parameters and no output schema, the description is minimally adequate but lacks detail on what the returned list contains (e.g., TV show objects, ordering). It meets the minimum for this low-complexity tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, clearly detailing the 'language' and 'timeWindow' parameters. The description adds no additional meaning beyond the schema, meeting the baseline expectation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Get') and the resource ('a list of trending TV shows'). However, it does not distinguish from the sibling tool 'get_trending_movies' beyond the resource name, missing an opportunity to clarify the difference.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like 'get_trending_movies' or 'search_tv_shows'. The agent must infer usage from the name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_tv_show_detailsB
Get detailed information about a specific TV show by its ID
| Name | Required | Description | Default |
|---|---|---|---|
| language | No | Language code (e.g. 'en-US', 'zh-CN') | |
| tvShowId | Yes | The ID of the TV show |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose behavioral traits such as whether the call is read-only, idempotent, or requires authentication. It only implies a read operation without further detail.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence that efficiently communicates the core functionality with no extraneous words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple data retrieval tool with well-documented schema parameters, the description is mostly complete. However, it could mention the type of details returned (e.g., cast, episodes) to fully set expectations given no output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, with both parameters having descriptions. The tool description adds no additional meaning or usage context beyond what the schema already provides, meeting the baseline for high coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves detailed information for a specific TV show by its ID, distinguishing it from sibling tools like get_movie_details (for movies) and search_tv_shows (for searching).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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 (e.g., search_tv_shows for finding shows by name, get_trending_tv for popular shows). The description implies usage only when a known TV show ID is available.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_moviesB
Search for movies on TMDB by title to get metadata like overview, release date, and rating
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | The movie title to search for | |
| region | No | Region code (e.g. 'US', 'FR') | |
| language | No | Language code (e.g. 'en-US', 'zh-CN') |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It fails to disclose behavioral traits such as pagination, rate limits, read-only nature, or response structure. Only a vague mention of metadata fields is given.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence that efficiently conveys the tool's action and output. It is front-loaded with the core purpose and avoids unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a search tool with no output schema, the description lacks details on result format, pagination, limit, or error handling. It only hints at returned fields but is insufficient for complete understanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage for all three parameters. The description adds minimal value beyond repeating the purpose of the 'query' parameter; it does not enrich understanding of 'region' or 'language' beyond their schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: searching for movies by title to retrieve metadata. It distinguishes itself from siblings like 'get_movie_details' and 'search_tv_shows' by specifying 'movies' and the search action.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not provide explicit guidance on when to use this tool versus alternatives, such as when to use 'get_movie_details' instead. No exclusion criteria or context for optimal use is mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_personA
Search for people (actors, directors, etc.) on TMDB
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | The name of the person to search for | |
| language | No | Language code (e.g. 'en-US', 'zh-CN') |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description only states the tool's function without disclosing behavioral traits such as rate limits, authentication requirements, result limits, or return format. This is insufficient for a search tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence that efficiently communicates the tool's purpose without unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having only two parameters with good schema descriptions, the tool lacks an output schema, and the description does not cover return values, pagination, or typical usage patterns. The minimal description is inadequate for a search tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, with both parameters clearly described in the input schema. The description adds no additional meaning beyond the schema, resulting in a baseline score of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Search for people (actors, directors, etc.) on TMDB', specifying the resource and examples. It effectively distinguishes from sibling tools which focus on movies, TV shows, or trending content.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for searching people by name, and sibling tool names (e.g., search_movies, search_tv_shows) provide clear context. However, no explicit when-not-to-use or alternative guidance is given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_tv_showsA
Search for TV shows on TMDB by title to get metadata like overview, first air date, and rating
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | The TV show title to search for | |
| language | No | Language code (e.g. 'en-US', 'zh-CN') |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It mentions output includes metadata like overview, first air date, and rating, but lacks details on pagination, result limits, or case sensitivity. Behavior is partially transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence of 18 words. It is front-loaded with key information and contains no unnecessary text.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema exists, so the description must explain return values. It lists three metadata fields but does not specify the structure (array of objects) or additional fields like poster_path, vote_average. Incomplete for a search tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%. The description restates that query is the title, adding little beyond the schema. Baseline 3 is appropriate as schema already documents both parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool searches for TV shows on TMDB by title, returning metadata like overview, first air date, and rating. It differentiates from siblings such as search_movies and search_person.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for searching TV shows by title but does not explicitly state when to use this tool versus alternatives like get_tv_show_details for full details or search_movies for movies. No exclusions or when-not-to-use guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
7 tool updates
v1.0.6- First observed
get_movie_details - First observed
get_trending_movies - First observed
get_trending_tv - First observed
get_tv_show_details - First observed
search_movies - First observed
search_person - First observed
search_tv_shows
TDQS
Each tool targets a distinct resource: movie details, TV details, trending movies, trending TV, search movies, search TV, and search people. No overlap exists.
All tools use a consistent verb_noun pattern in snake_case (e.g., get_movie_details, search_movies, search_person), making the naming predictable.
7 tools is well-scoped for a TMDB server, covering search, details, trending, and people without being excessive or insufficient.
Covers core workflows (search, details, trending) for both movies and TV, plus people search. Missing credits, recommendations, or genres, but not critically incomplete.
Maintenance
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