SteamData-FeedbackExtractor

Introduction

Content creation in the digital sphere involves generating and distributing various media for intended audiences. This specific tool assists creators by systematically gathering established player sentiment data concerning video games. Content, defined as material expressed through a medium like writing or digital arts, benefits from structured feedback analysis for self-expression or publication purposes.

Extra Details

The underlying mechanism for obtaining this material frequently interfaces with official distribution channels, which inherently involve considerations like data privacy and adherence to platform moderation policies regarding content distribution. The summaries generated distill large volumes of user commentary into manageable formats.

Setup

Installation for utilizing this service within a Model Context Protocol environment can be managed automatically through the Smithery service installation utility. Execute the following command line sequence within your terminal environment to deploy the component for use with Claude Desktop clients:

npx -y @smithery/cli install @fenxer/steam-review-mcp --client claude

Alternatively, direct execution using npx is possible, or the service definition can be embedded within your configuration file structure like this:

{
  "mcpServers": {
    "steam-review-mcp": {
      "command": "npx",
      "args": [
        "steam-review-mcp"
      ]
    }
  }
}

If you wish to run the underlying service directly, employ this command:

npx steam-review-mcp

Usage

This MCP service exposes the get_steam_review function for fetching game statistics and player commentary when provided with a valid Steam application ID.

Further technical documentation regarding the data structures is derived from the Steamworks API section concerning user review retrieval processes User Reviews - Get List.

The data returned from a successful query is structured into two primary components, providing comprehensive insight.

1. game_reviews:
2. success: Indicates the operational status of the data retrieval.
3. review_score: The aggregated numerical rating achieved by the title.
4. review_score_desc: A textual description corresponding to the aggregated rating.
5. total_positive: Count of all favorable assessments submitted by users.
6. total_negative: Count of all unfavorable assessments submitted by users.

7. reviews: Contains the raw text bodies of the collected player feedback entries.

8. game_info:

9. name: The official designation of the video game product.
10. detailed_description: Extended textual explanation of the game's features.

summarize-reviews

This specific tool function is designed to perform a high-level analytical assessment of all available game reviews. Its output synthesizes the primary advantages and known disadvantages of the product.

Parameters

• appid (required): The unique numeric identifier assigned by Steam; for example, input 570 corresponds to Dota 2.

recent-reviews-analysis

This function targets current player sentiment by examining the most recent submissions. It summarizes the contemporary status of the game according to its community.

Parameters

• appid (required): The Steam game ID required for fetching records; for instance, use 570 for Dota 2.

Development

Procedures for maintaining or extending this service component involve standard software development lifecycle steps. These steps include managing necessary dependencies, compiling the source code, and initiating the service runtime.

Install necessary dependencies using this command:

npm install

Compile the project assets with the following instruction:

npm run build

To start the local service instance for testing or operation, use:

npm start

Related Topics

• Digital Media Production
• Platform Moderation Policies
• User-Generated Content (UGC)
• Steamworks API Documentation
• Misinformation Challenges in Online Spaces

Conclusion

By automating the extraction and structuring of community feedback, this utility streamlines a necessary step for content creators. Analyzing these digital contributions helps refine narratives, adjust marketing focuses, or simply document player perception accurately across various digital distribution vectors.