mcp-appstore
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 11 tools
Most tools have clearly distinct purposes targeting different app store data aspects like reviews, keywords, app details, developer info, pricing, similar apps, and version history. However, 'analyze_reviews' and 'analyze_top_keywords' could potentially overlap with 'fetch_reviews' and 'get_keyword_scores' in functionality, creating minor ambiguity about whether they perform retrieval or analysis.
All tool names follow a consistent snake_case pattern with clear verb_noun structures. The naming convention is uniform throughout, using verbs like 'analyze', 'fetch', 'get', and 'search' paired with specific nouns, making the set highly predictable and readable.
With 11 tools, the count is well-scoped for an app store analysis server. Each tool appears to serve a distinct data retrieval or analysis function, covering categories, reviews, keywords, app details, and more, without feeling excessive or insufficient for the domain.
The tool set provides comprehensive coverage for app store data analysis, including search, details, reviews, keywords, pricing, developer info, similar apps, and version history. A minor gap exists in update or modification tools (e.g., for tracking changes), but the surface supports core analysis workflows effectively.