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jhomen368

Steam Reviews MCP

by jhomen368
OverviewSchemaRelated ServersScoreDiscussions
TypeScript
Hybrid

Server Quality Checklist

67%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v1.0.1

  • Disambiguation5/5

    Each tool has a clearly distinct purpose: analyze_reviews focuses on sentiment and theme analysis, fetch_reviews retrieves raw review data, get_game_info provides game metadata, and search_steam_games handles game discovery. There is no overlap in functionality that would cause confusion.

    Naming Consistency4/5

    The tools follow a consistent verb_noun pattern (analyze_reviews, fetch_reviews, get_game_info, search_steam_games), with all using snake_case. The minor deviation is 'get_game_info' using 'get' while others use more specific verbs like 'analyze' or 'fetch', but this is still readable and coherent.

    Tool Count5/5

    With 4 tools, the set is well-scoped for the server's purpose of accessing Steam reviews and game data. Each tool serves a distinct, essential function without bloat, covering analysis, data retrieval, game info, and search effectively.

    Completeness4/5

    The tool set covers core workflows for Steam reviews and game info, including analysis, fetching, metadata retrieval, and search. A minor gap is the lack of tools for user-specific operations (e.g., fetching user profiles or managing reviews), but the domain is well-covered for general use cases.

  • Average 3.6/5 across 4 of 4 tools scored. Lowest: 2.9/5.

    See the Tool Scores section below for per-tool breakdowns.

    • No community issues in the last 6 months
    • 35 commits in the last 12 weeks
    • Last stable release on
    • No critical vulnerability alerts
    • No high-severity vulnerability alerts
    • No code scanning findings
    • CI is passing

  • This repository is licensed under MIT License.

  • This repository includes a README.md file.

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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

  • Behavior2/5

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

    No annotations provided, so description carries full burden. It mentions returns review text, author info, timestamps, voting data, and supports time-bounded queries and review bomb filtering. However, it does not disclose side effects, auth requirements, rate limits, or data freshness. Minimal transparency beyond parameter descriptions.

    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?

    Two sentences covering main action and key features. No wasted words. Could be improved by front-loading essential info more clearly, but sufficiently concise for a tool with many parameters.

    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?

    Description provides a high-level overview of what the tool does and its capabilities. However, it lacks details about output format, pagination mechanics, or error handling. Given the complexity (10 params, no output schema), more context would help an agent use it effectively.

    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?

    Schema description coverage is 100%, so baseline is 3. Description adds high-level context ('advanced filtering and pagination support') but does not provide significant additional meaning beyond the detailed schema descriptions for each parameter.

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

    Purpose5/5

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

    Description clearly states 'Fetch actual user reviews for a Steam game' with specific verb and resource. It distinguishes from sibling tools like analyze_reviews and get_game_info by mentioning advanced filtering and pagination.

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

    Usage Guidelines3/5

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

    Description implies usage for fetching reviews with filters, but does not explicitly state when to use this tool vs siblings like analyze_reviews or search_steam_games. No when-not-to-use or alternative guidance provided.

    Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

  • Behavior3/5

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

    With no annotations, the description provides some behavioral detail (batch support, returned fields) but lacks info on rate limits, concurrency, or behavior on no results. Adequate but not comprehensive.

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

    Conciseness5/5

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

    Two concise sentences, front-loaded with core purpose. Every word contributes without redundancy.

    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?

    No output schema, so description should clarify return structure more. Mentions fields but not format or pagination. Adequate for a simple search tool but incomplete.

    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?

    Schema coverage is 100%, so baseline is 3. The description adds some context ('per query' for limit) but mostly repeats schema descriptions. Minimal added value.

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

    Purpose5/5

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

    Clearly states verb (search), resource (Steam games), method (by name or keywords), and returned information (AppID, name, price, preview image). Distinct from sibling tools like analyze_reviews or get_game_info.

    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?

    No explicit guidance on when to use this tool versus alternatives. While it mentions single or batch queries, there is no advice on when to choose batch over single or situations where this tool is inappropriate.

    Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

  • Behavior2/5

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

    No annotations provided, so description is the sole source. It mentions pre-fetched reviews avoid duplicate API calls, but does not disclose other behavioral traits like read-only nature, rate limits, or side effects.

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

    Conciseness5/5

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

    Two clear sentences, front-loaded with main purpose. No redundant information.

    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?

    With 9 parameters and no output schema, the description covers high-level features but does not explain output format or 'key insights'. Adequate but not fully comprehensive.

    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?

    Schema coverage is 100%, so baseline is 3. The description summarizes parameter categories (topic drill-down, time-bounded, pre-fetched) but adds no new meaning beyond the schema descriptions.

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

    Purpose5/5

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

    The description clearly states the tool fetches and analyzes Steam game reviews, extracting sentiment, themes, and insights. It distinguishes from siblings like fetch_reviews by combining both actions.

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

    Usage Guidelines4/5

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

    The description mentions optional features (topic drill-down, time-bounded analysis, pre-fetched reviews) but does not explicitly state when to use vs. alternatives. Context from siblings implies separation of concerns.

    Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

  • Behavior2/5

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

    No annotations exist, so the description must disclose behavioral traits. It does not mention side effects, rate limits, permissions, or data freshness. The operation is read-only but that is implied. Lacks necessary behavioral context for safe agent invocation.

    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 concise, front-loaded with the core purpose, and uses efficient language. It could be slightly more structured (e.g., bullet points) but remains clear and avoids unnecessary verbosity.

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

    Completeness4/5

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

    With no output schema, the description adequately explains return values (list of data fields). It covers the main parameters and optional includes. Minor gaps like pagination or error handling are absent, but overall complete for a game info retrieval tool.

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

    Parameters4/5

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

    Schema coverage is 100%, but the description adds meaning by listing the type of returned data (e.g., 'description, price, developers, publishers, platforms, metacritic score, review statistics') and explaining optional includes and filtering criteria. This adds context beyond the schema's parameter descriptions.

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

    Purpose5/5

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

    The description clearly states 'Get detailed information about one or more Steam games by AppID' and lists specific data fields (description, price, developers, etc.). It distinguishes from siblings like analyze_reviews and search_steam_games by focusing on retrieving comprehensive game data for given AppIDs.

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

    Usage Guidelines3/5

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

    The description implies use when you have AppIDs and want detailed info, but provides no explicit guidance on when to use alternatives (e.g., search_steam_games for discovering AppIDs). No exclusions or when-not-to-use context is given.

    Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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