tv-recommender-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
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 12 tools
Most tools have distinct purposes targeting different aspects of TV shows (discovery, details, recommendations, providers), though 'discover_shows' and 'get_popular_shows'/'get_trending_shows' could potentially overlap in some contexts. The clear naming helps differentiate them.
All tools follow a consistent verb_noun pattern with 'get_' or 'find_'/'discover_' prefixes, using snake_case throughout. This makes the tool set predictable and easy to navigate for an agent.
12 tools is well-scoped for a TV recommender server, covering discovery, details, recommendations, and supplementary information without being overwhelming. Each tool appears to serve a specific function in the domain.
The tool set covers key areas like discovery, details, recommendations, and providers, but lacks explicit CRUD operations for user preferences or watch history, which might be expected in a recommender system. However, the core TV show information surface is largely complete.