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pixfishx

MCP Epic Free Games

by pixfishx
OverviewSchemaRelated ServersScoreDiscussions
Python
Remote

Server Quality Checklist

58%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v0.1.2

  • Disambiguation5/5

    The two tools have clearly distinct purposes: one retrieves currently free games, while the other retrieves upcoming free games. There is no overlap in functionality, making it easy for an agent to select the appropriate tool based on the temporal context needed.

    Naming Consistency5/5

    Both tools follow a consistent verb_noun pattern with 'get' as the verb and descriptive nouns ('now_free_games', 'upcoming_free_games'). The naming is uniform and predictable, using snake_case throughout without any deviations.

    Tool Count2/5

    With only 2 tools, the server feels thin for its apparent domain of Epic Games free games. While it covers current and upcoming games, there are likely gaps such as historical free games, game details, or filtering options that could enhance functionality, making the tool count borderline inadequate.

    Completeness3/5

    The server covers the basic temporal aspects of free games (current and upcoming), but there are notable gaps. For example, it lacks tools for getting detailed information about specific games, filtering by genre or platform, or accessing past free games, which limits the agent's ability to handle more complex queries in this domain.

  • Average 3.2/5 across 2 of 2 tools scored.

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

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  • 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?

    With no annotations provided, the description carries the full burden of behavioral disclosure. It states what the tool does but doesn't describe traits like whether it's read-only, rate-limited, requires authentication, or what the return format might be. This is a significant gap for a tool with zero annotation coverage.

    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?

    The description is a single, efficient sentence that front-loads the core purpose without any wasted words. It's appropriately sized for a simple tool with no parameters.

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

    Completeness2/5

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

    Given the lack of annotations and output schema, the description is incomplete. It doesn't explain behavioral traits, return values, or how it differs from its sibling tool. For a tool with no structured data beyond the input schema, more context is needed to be fully helpful.

    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?

    The tool has 0 parameters with 100% schema description coverage, so the schema fully documents the inputs. The description doesn't need to add parameter information, and it appropriately doesn't mention any. Baseline 4 is correct for zero-parameter tools.

    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 action ('Get') and resource ('upcoming free games from Epic Games Store'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from its sibling tool 'get_now_free_games', which appears to fetch currently free games versus upcoming ones.

    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 guidance is provided on when to use this tool versus its sibling 'get_now_free_games'. The description implies usage for upcoming games but doesn't specify context, alternatives, or exclusions, leaving the agent to infer the distinction.

    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 are provided, so the description carries the full burden of behavioral disclosure. It states what the tool does but does not describe any behavioral traits such as rate limits, authentication needs, data freshness, or response format. This leaves significant gaps for an agent to understand how to interact with the tool effectively.

    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?

    The description is a single, clear sentence that directly states the tool's purpose without any unnecessary words. It is front-loaded and efficiently communicates the essential information, making it highly concise and well-structured.

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

    Completeness2/5

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

    Given the lack of annotations and output schema, the description is incomplete. It does not provide enough context about the tool's behavior, such as what data is returned, how it is formatted, or any operational constraints. For a tool with no structured support, the description should offer more guidance to be fully helpful.

    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?

    The tool has zero parameters, and the schema description coverage is 100%, so there are no parameters to document. The description does not need to add parameter semantics, and it appropriately avoids mentioning any. A baseline score of 4 is applied as per the rules for zero parameters.

    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 verb ('Get') and resource ('currently free games from Epic Games Store'), making the purpose immediately understandable. It distinguishes from the sibling tool 'get_upcoming_free_games' by specifying 'currently' versus 'upcoming', though this differentiation is implicit rather than explicit.

    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 usage context by specifying 'currently free games', which suggests it should be used for real-time or recent data rather than future projections. However, it does not explicitly state when to use this tool versus the sibling 'get_upcoming_free_games' or provide any exclusions or alternatives.

    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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