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abaiii168

World Cup 2026 MCP Server

by abaiii168

Server Quality Checklist

75%
Profile completionA complete profile improves this server's visibility in search results.
  • Latest release: v0.1.1

  • Disambiguation5/5

    Each tool has a clearly distinct purpose: dataset returns full metadata and all fixtures, match by id, matches with filtering, metadata for API info, and next match. No overlap.

    Naming Consistency5/5

    All tools follow the exact pattern 'get_world_cup_2026_<specific>', using snake_case consistently. Very predictable.

    Tool Count5/5

    5 tools is appropriate for a focused World Cup 2026 fixture server. It covers retrieval of all data, single match, filtered list, metadata, and next match without being excessive.

    Completeness5/5

    The tool set covers all common retrieval needs for a fixture data source: getting all fixtures, by ID, filtered, next match, and metadata. No obvious gaps given the read-only domain.

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

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

    • 0 of 1 community issues answered or closed in the last 6 months
    • 8 commits in the last 12 weeks
    • No stable releases found
    • 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 are provided; the description mentions it uses a public schedule API and allows time zone conversion, but does not disclose behavior such as error handling if no upcoming match exists, rate limits, or response format.

    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, well-structured sentence that is front-loaded with the action and resource, containing no extraneous 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?

    The tool is simple with one optional parameter and no output schema; the description covers purpose and timezone but omits any indication of the return structure, which would be helpful for an agent.

    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 single parameter timezone is fully described in the input schema with examples and default; the description adds no extra meaning beyond the schema, so baseline score of 3 is appropriate.

    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 the tool returns the nearest upcoming World Cup 2026 fixture, specifying the source and time zone parameter, distinguishing it from siblings that may return multiple matches or require identifiers.

    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 it is for the single next match, but does not explicitly state when to use this tool versus alternatives like get_world_cup_2026_matches or get_world_cup_2026_match.

    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?

    Description lists returned data fields (teams, venue, stage, kickoff, links), but without annotations, it lacks disclosure on authentication, rate limits, or error handling. Covers main behavior but not edge cases.

    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 is concise, front-loaded with the action, and contains no superfluous information.

    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?

    For a simple retrieval tool with no output schema, the description adequately lists all key return fields. Minor gaps like error handling or link details do not significantly impair completeness.

    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% with detailed parameter descriptions. The description does not add significant extra meaning beyond the schema, meeting baseline.

    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 'Return one World Cup 2026 fixture by match id', using a specific verb and resource. It distinguishes from sibling tools like get_world_cup_2026_matches which returns multiple 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. Sibling tools are listed but no conditions or exclusions are 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?

    No annotations exist, so description carries full burden. It mentions time zone conversion but omits other behavioral traits like data freshness, error conditions, or if results are static. 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?

    Single sentence of 18 words, front-loaded with purpose, no fluff. Efficiently communicates core functionality.

    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 and moderate complexity. Description covers filtering but does not hint at return format, ordering, or data volume. Could be improved with brief note on match object fields.

    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 80%, so parameters are mostly documented. The description adds little beyond restating filter options; it confirms time zone handling already implied by parameter descriptions. No new semantics.

    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 verb 'Return' and the resource 'fixtures' with specific filters (time zone, stage, group, team). It distinguishes from siblings like get_world_cup_2026_match (singular) and get_world_cup_2026_dataset (broader).

    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 when to use (for filtered match list), but does not explicitly state when not to use or mention alternatives among siblings. Some guidance on selecting this tool over others is missing.

    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?

    No annotations are provided, so the description carries full burden. It discloses that the tool returns metadata, attribution, endpoint links, and schema notes, which implies a read-only operation. However, it does not explicitly state that it is safe or idempotent, nor does it mention any side effects or authentication requirements.

    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 sentence that front-loads the key action and contents. Every word is purposeful, with no redundancy or filler.

    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?

    For a tool with no parameters and no output schema, the description is adequate. It lists the types of information returned. However, it could be improved by specifying the format (e.g., JSON) or noting that it pertains to the free public API.

    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 input schema has zero parameters, and schema_description_coverage is 100%, so the baseline is 4. The description does not need to add parameter details, as there are none.

    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 it returns metadata, attribution, endpoint links, and schema notes. It identifies the tool as a metadata retrieval for the World Cup 2026 API, distinguishing it from sibling tools that retrieve datasets, matches, or next matches.

    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 that this tool should be used to obtain metadata before making other API calls, but it does not explicitly state when to use it versus alternatives or provide exclusions. No guidance on prerequisites or context is given.

    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 carries full burden. It discloses the output format (JSON-LD) and includes details like 104 fixtures and UTC timezone. However, it lacks information on potential behavioral aspects like data freshness, caching, or authentication needs.

    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 key information: return type, content, and use cases. Every word contributes meaning without redundancy.

    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 tool's simplicity (no parameters, no output schema, no nested objects), the description adequately covers what the tool returns and its purpose. No additional context is necessary for an agent to understand and invoke it.

    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 input schema is empty. The description correctly adds no parameter details, which is appropriate. According to guidelines, baseline for 0 parameters is 4.

    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 returns 'Dataset JSON-LD metadata and all 104 public fixtures in UTC,' specifying both content and format. It distinguishes from siblings that focus on individual matches, multiple matches, or metadata only.

    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 indicates usage for 'citation, indexing, or data-directory use,' which implies when to choose this tool over siblings. However, it does not explicitly state when not to use it or name 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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