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Steam Review MCP

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Access Steam game reviews using Model Context Protocol (MCP).

MCP Badge

Install MCP Server

Features

Helps LLMs retrieve Steam game reviews and information:

  • Get game reviews (positive/negative counts, review scores, review content, etc.)

  • Get game basic information (name, detailed description)

  • Analyze game reviews and summarize pros and cons

Related MCP server: mcp-server-steam

Installation

Installing via Smithery

To install Steam Review for Claude Desktop automatically via Smithery:

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

Run it directly with npx:

npx steam-review-mcp

or add:

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

Usage

Tools

This MCP service provides the get_steam_review tool, which retrieves reviews and game information by passing a Steam game appid.

For more details, check the Steamwork API: User Reviews - Get List

The returned data contains two parts:

  1. game_reviews:

    • success: Whether the query was successful

    • review_score: Review score

    • review_score_desc: Review score description

    • total_positive: Total positive reviews

    • total_negative: Total negative reviews

    • reviews: All review text content (without other metadata)

  2. game_info:

    • name: Game name

    • detailed_description: Detailed game description

Prompts

summarize-reviews

For overall game review analysis, summarizing the pros and cons of the game.

Parameters
  • appid (required): Steam game ID, e.g., 570 (Dota 2)

recent-reviews-analysis

For analyzing recent game reviews, summarizing the current state of the game and player feedback.

Parameters
  • appid (required): Steam game ID, e.g., 570 (Dota 2)

Development

# Install dependencies
npm install

# Build project
npm run build

# Run service
npm start

Available Tools

1 tool
get_steam_reviewC

Retrieves reviews and game information for a specific Steam application. Returns formatted review data including review scores, positive/negative counts, review texts, and basic game information.

ParametersJSON Schema
NameRequiredDescriptionDefault
appidYesSteam application ID
filterNorecent: sorted by creation time, updated: sorted by last updated time,all: (default) sorted by helpfulness, with sliding windows based on day_range parameter, will always find results to return.all
languageNoLanguage filter (e.g. english, french, schinese). Default is all languages.all
day_rangeNorange from now to n days ago to look for helpful reviews. Only applicable for the all filter.
cursorNoreviews are returned in batches of 20, so pass * for the first set, then the value of cursor that was returned in the response for the next set, etc. Note that cursor values may contain characters that need to be URLEncoded for use in the querystring.*
review_typeNoall:all reviews (default), positive: only positive reviews, negative: only negative reviewsall
purchase_typeNoall: all reviews, non_steam_purchase: reviews written by users who did not pay for the product on Steam,steam: reviews written by users who paid for the product on Steam (default)steam
num_per_pageNonumber of reviews to get, max 100, default 50

TDQS

C2.9/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions that the tool 'returns formatted review data' including specific elements like scores and texts, which is helpful. However, it lacks critical behavioral details such as rate limits, authentication requirements, error conditions, or whether this is a read-only operation (though 'retrieves' implies it).

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is appropriately concise with two sentences that efficiently convey the purpose and return value. The first sentence states what the tool does, and the second describes the return format. There's no unnecessary repetition or verbose language, though it could be slightly more structured with explicit sections.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's moderate complexity (8 parameters, no output schema, no annotations), the description is minimally adequate. It covers the basic purpose and return format but lacks important contextual information about behavioral traits, error handling, and usage scenarios. The absence of an output schema means the description should ideally explain the return structure more thoroughly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema description coverage is 100%, meaning all parameters are well-documented in the schema itself. The description adds minimal value beyond the schema by mentioning 'basic game information' which isn't explicitly in the parameter documentation, but doesn't provide additional parameter context or usage examples. This meets the baseline for high schema coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: retrieving reviews and game information for a specific Steam application. It specifies the verb 'retrieves' and resource 'reviews and game information', and distinguishes the scope with 'for a specific Steam application'. However, it doesn't differentiate from siblings since none exist, preventing a perfect score.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. There are no explicit statements about appropriate contexts, prerequisites, or exclusions. While no sibling tools exist, the description fails to mention any usage scenarios or constraints beyond what's implied by the purpose.

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.

  1. 1 tool update
    • First observedget_steam_review

TDQS

B3.1/5.0
Disambiguation5/5

With only one tool, there is no possibility of ambiguity or overlap between tools. The tool has a clear, distinct purpose focused on retrieving Steam review data.

Naming Consistency5/5

A single tool inherently has perfect naming consistency, as there are no other tools to compare it against. The name 'get_steam_review' follows a clear verb_noun pattern.

Tool Count2/5

One tool is too few for a server named 'Steam Review MCP', which suggests a broader scope for interacting with Steam reviews. This minimal set severely limits functionality, such as lacking search, filtering, or update capabilities.

Completeness2/5

The tool surface is severely incomplete for a Steam review domain. It only provides retrieval for a specific application, missing essential operations like searching reviews, getting user reviews, updating data, or handling multiple games, which are typical for such a service.

Maintenance

ActivityInactive
ResponsivenessNo issues

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