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sanketjoshi2012

FIFA World Cup 2026 MCP Server

Server Quality Checklist

58%
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  • Latest release: v0.1.0

  • Disambiguation5/5

    Each tool has a clearly distinct purpose: all results, specific match, standings, today's matches. No overlap or ambiguity.

    Naming Consistency5/5

    All tools follow a consistent 'get_' prefix with descriptive nouns using snake_case, e.g., get_all_results, get_match_result.

    Tool Count3/5

    With only 4 tools, the server is relatively sparse but still covers basic querying needs for a focused domain. Slightly under-scoped but reasonable.

    Completeness2/5

    Missing key operations like team-specific schedules, group details, or upcoming match queries beyond today. The surface has notable gaps for comprehensive coverage.

  • Average 3.8/5 across 4 of 4 tools scored.

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

    • No community issues in the last 6 months
    • 5 commits in the last 12 weeks
    • No stable releases found
    • No critical vulnerability alerts
    • No high-severity vulnerability alerts
    • No code scanning findings
    • CI status not available
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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?

    No annotations are present, so the description must carry the full burden. It only mentions 'get all results' and an optional filter, with no disclosure of behavioral traits like sorting, pagination, error handling, or idempotency. This is minimal.

    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 extremely concise at two sentences, with the purpose front-loaded in the first sentence. Every word is necessary; no wasted text.

    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?

    Given the tool's simplicity (one optional parameter) and the presence of an output schema, the description covers the essential functionality. However, it could mention return value structure or ordering, but it's mostly complete for a get-all 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 description coverage is 0%, so the description compensates by providing examples of valid round_name values like 'Quarter-final' or 'Group A'. This adds meaning beyond the raw schema.

    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 all World Cup 2026 results' with an optional filter, which specifies the verb, resource, and scope. This distinguishes it from siblings like get_match_result (specific match) and get_standings (standings).

    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 alternatives. The description only states what it does, not when to prefer it over get_match_result, get_standings, or get_todays_matches.

    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 carries full burden, but it only says 'get' without disclosing any behavioral details like data freshness, caching, or restrictions.

    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?

    Single sentence that clearly conveys the tool's purpose with no wasted words.

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

    Completeness5/5

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

    Given the low complexity and existence of output schema, the description sufficiently informs the agent what the tool does.

    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?

    Input schema has zero parameters with 100% coverage. Description adds no additional parameter meaning, but baseline is 4 for no parameters.

    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 verb 'Get' and resource 'FIFA World Cup 2026 group stage standings', which is specific and distinct from sibling tools like get_all_results, get_match_result, and get_todays_matches.

    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. Lacks any when/when-not or context indications.

    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. It does not disclose behavioral traits such as timezone handling, whether it includes only completed matches, rate limits, or behavior when no matches are scheduled today. This leaves significant unknowns for an agent.

    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?

    Single sentence, no wasted words, front-loaded with key information. Perfectly concise for a zero-parameter tool.

    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?

    Given zero parameters and an output schema (present but not shown), the description is mostly complete. However, it could mention timezone or data freshness; still, it is adequate for a simple 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?

    Tool has no parameters, so schema coverage is 100% by default. The description adds useful context about return data (scores and goals), justifying a score above baseline 3.

    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 retrieves all FIFA World Cup 2026 matches happening today with scores and goals, specifying the resource, filter, and data. It distinguishes from siblings like get_all_results and get_match_result.

    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 for today's matches but does not explicitly state when to use this tool versus alternatives like get_all_results (all matches) or get_match_result (single match). No exclusions or when-not-to-use guidance.

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

  • Behavior4/5

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

    No annotations are provided, so the description carries the burden. It clearly indicates the tool returns result and goals, implying read-only behavior. No side effects or limitations are mentioned, but for a simple data retrieval tool, this is sufficiently transparent.

    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 of 15 words. It is front-loaded with the action ('Get') and directly conveys the purpose without extraneous information. Every word earns its place.

    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?

    Given the presence of an output schema, the description need not detail return values. It covers the core functionality and distinguishes the tool from siblings. However, it lacks guidance on error handling or valid team names, which would improve completeness.

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

    Parameters2/5

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

    Schema description coverage is 0%, meaning no parameter descriptions exist. The tool description only adds that parameters are team names, without specifying format (e.g., full name, code) or any constraints. This minimal addition does not sufficiently compensate for the lack of 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 retrieves the result and goals for a specific World Cup match identified by two teams. It distinguishes itself from sibling tools like get_all_results (all matches) and get_standings (standings) by focusing on a single match.

    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 need a result for a specific pair of teams, but it does not explicitly tell the agent when to choose this tool over siblings like get_all_results or get_todays_matches. The usage context is inferred but not directly stated.

    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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