Movie Search MCP Server
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Server capabilities have not been inspected yet.
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| search_moviesD | – |
| get_movie_detailsD | – |
| recommend_moviesD | – |
| popular_moviesD | – |
| movie_helpD | – |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 5 tools
The tools have distinct names suggesting different purposes (details, help, popular, recommend, search), but without descriptions, there's potential ambiguity. For example, 'popular_movies' and 'recommend_movies' might overlap in functionality if recommendations are based on popularity, and 'movie_help' is vague and could be confused with other tools. The naming helps, but descriptions would be needed to fully disambiguate.
The naming follows a consistent pattern with snake_case and a mix of verb_noun (e.g., 'get_movie_details', 'search_movies') and noun_verb (e.g., 'movie_help', 'popular_movies', 'recommend_movies'). There are minor deviations in word order, but overall it's readable and mostly predictable, with no chaotic mixing of styles.
With 5 tools, this is well-scoped for a movie search server. It covers key operations like searching, getting details, finding popular movies, and recommendations, which aligns with typical movie-related functionalities. The count is appropriate, not too thin or heavy for the apparent domain.
The tool set covers basic search and discovery functions (search, details, popular, recommend), but there are notable gaps. For a movie domain, missing operations might include user-specific actions (e.g., rate_movie, add_to_watchlist), filtering or sorting options, or genre-based searches. The surface is functional but incomplete for a full movie experience, likely causing some agent limitations.