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Mooooooon

hltv-csgo-mcp

by Mooooooon

Server Quality Checklist

67%
Profile completionA complete profile improves this server's visibility in search results.
  • Latest release: v0.1.3

  • Disambiguation5/5

    Each tool has a distinct purpose: search entities, list matches, and get match details. There is no overlap or ambiguity in their intended use. The descriptions clearly separate the search/filter/get workflow.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun pattern: search_hltv_entities, list_hltv_matches, get_hltv_match. The verb clearly indicates the action and the noun indicates the resource, making the pattern predictable.

    Tool Count4/5

    Three tools is on the lower end but still appropriate for a focused HLTV match data server. The set covers the core workflow of search, list, and detail without feeling excessive. A few more tools could be justified, but the current count is reasonable.

    Completeness4/5

    The tools cover the primary workflow: finding entities, listing matches, and retrieving match details. Missing are direct event or player detail endpoints, but search_hltv_entities provides entity discovery. The core match lifecycle appears adequately covered with minor gaps.

  • Average 4.1/5 across 3 of 3 tools scored.

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

    • No community issues in the last 6 months
    • 7 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
  • 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

  • Behavior3/5

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

    Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds the match categories and filter types, which is useful but not deeper behavioral traits like pagination or rate limits. No contradiction with annotations.

    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 sentences: the first front-loads the core purpose, the second lists filter options. No redundant or wasted words.

    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 complexity (6 optional params, output schema, annotations), the description is sufficient: it states what it does and the main filters. It doesn't mention defaults for kind/limit, but those are in the schema. Acceptable for a list tool.

    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 high (83%), so baseline is 3. The description summarizes the filter parameters (team, event, date, limit) but adds little beyond the schema, except emphasizing 'exact team display name' and referencing event IDs from search_hltv_entities.

    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 lists Counter-Strike matches from HLTV.org, with a specific verb 'List' and resource. It enumerates filters (team, event, date range, limit) that distinguish it from sibling tools like get_hltv_match and search_hltv_entities.

    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?

    Provides clear context on the tool's scope (upcoming/live/finished matches) and filter options. However, it does not explicitly mention when to use this over get_hltv_match or how to obtain event IDs, though the schema references search_hltv_entities.

    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?

    Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, covering safety behavior. The description adds the workflow context (search before filtering) but does not disclose additional behavioral traits such as fuzzy matching, result ordering, pagination, or rate limits. With strong annotations, a moderate score is appropriate.

    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 two sentences, front-loaded with the action and followed by the use-case guidance. There is no redundancy or filler; every word contributes meaning.

    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, a rich output schema, and comprehensive annotations, the description is largely complete: it names the domain, entity types, and a key workflow. It omits details like result format or edge-case behavior, but those are covered by the output schema and annotations, so the description suffices.

    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 provides descriptions for 'query' and 'types', covering 67% of parameters, but 'limit' lacks a prose description. The description text itself adds no parameter-level detail beyond what the schema already says, and the term 'teams, players, or events' simply aligns with the types enum. This is adequate but not enhanced.

    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 searches HLTV.org for Counter-Strike teams, players, or events, which is a specific verb+resource+scope. It also distinguishes from sibling tools by positioning itself as a pre-filtering step for matches when the exact display name is unknown.

    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 explicitly indicates when to use the tool ('Use this before filtering matches by team when the exact HLTV display name is not already known'), providing a clear usage context. However, it stops short of naming alternative tools (e.g., list_hltv_matches) or stating when not to use it beyond the known-name condition.

    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?

    Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds value by enumerating the exact data fields returned (teams, score, event, start time, maps, streams), which is useful context beyond the structured annotations.

    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, direct sentence that front-loads the core purpose and the source of the required input. Every clause adds information; there is no wasted wording or repetition of annotations.

    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 low complexity (one parameter), the presence of an output schema, and the annotations covering safety, the description provides a complete summary of what the tool does and how to use it correctly. It mentions the exact data fields returned, which complements the output schema without redundancy.

    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 input schema already fully documents the single 'url' parameter with a description, so the baseline is 3. The tool description does not add further parameter semantics; it only repeats the fact that the URL comes from list_hltv_matches, which is already in the schema description. Schema coverage is 100%, so no additional compensation is needed.

    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 uses a specific verb ('Get') and clearly identifies the resource (one HLTV match page) and the key data returned (teams, score, event, start time, maps, streams). It also references the sibling tool list_hltv_matches, making the scope obvious and distinguishing it from the other sibling search_hltv_entities.

    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 provides clear context by stating it operates on an 'exact match URL returned by list_hltv_matches', implying a prerequisite to call list_hltv_matches first. However, it does not explicitly state when not to use alternatives like search_hltv_entities, so it lacks explicit exclusions.

    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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