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KTTechUp-Team304

VA-MCP

by KTTechUp-Team304
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Python
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Server Quality Checklist

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

  • Latest release: v0.1.0

  • Disambiguation5/5

    The two tools have completely distinct purposes: one lists supported checks (a domain-specific operation) and the other checks server status (a general utility). There is no overlap or ambiguity between them.

    Naming Consistency5/5

    Both tools follow a consistent snake_case naming pattern with clear verb_noun structure: 'list_supported_checks' and 'ping'. The naming is predictable and readable throughout.

    Tool Count2/5

    With only two tools, the server feels severely under-scoped for a domain like 'VA-MCP' (which suggests vulnerability assessment or similar). A single domain-specific tool plus a ping utility is too thin for meaningful agent workflows.

    Completeness2/5

    The server appears to target vulnerability/security checks, but only lists supported checks without tools to run checks, get results, or manage them. This leaves significant gaps that will hinder agent operations in this domain.

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

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

    • No community issues in the last 6 months
    • 54 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 provided, so the description carries the full burden of behavioral disclosure. It states the tool returns a list, implying a read-only operation, but doesn't specify details like response format, potential errors, rate limits, or authentication requirements. For a tool with zero annotation coverage, this leaves significant gaps in understanding its behavior beyond the basic action.

    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 directly states the tool's function without any unnecessary words or fluff. It is front-loaded with the core action and resource, making it easy to parse and understand quickly.

    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?

    Given the tool's simplicity (0 parameters, no output schema, no annotations), the description is adequate for conveying the basic purpose. However, it lacks details on output format or behavioral traits, which could be helpful for an agent to understand what to expect from the response. It meets the minimum viable level but doesn't provide comprehensive context.

    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, and the schema description coverage is 100% (as there are no parameters to describe). The description doesn't need to add parameter semantics, so it meets the baseline for this scenario. No additional value is required or provided, which is appropriate given the lack of 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 tool's purpose: '현재 지원 예정인 점검 항목 목록을 반환한다' translates to 'Returns a list of inspection items currently scheduled for support.' This specifies the verb ('returns') and resource ('list of inspection items scheduled for support'), making the purpose clear. However, it doesn't explicitly differentiate from the sibling tool 'ping', which likely serves a different function (e.g., connectivity testing), so it doesn't reach the highest score.

    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?

    The description provides no guidance on when to use this tool versus alternatives. It doesn't mention the sibling tool 'ping' or any other context for usage, such as prerequisites or scenarios where this tool is appropriate. Without such information, the agent lacks explicit direction on tool selection.

    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 full burden for behavioral disclosure. The description only states what the tool does ('checks server status') but provides no information about what the check entails, what 'status' means, whether this is a read-only operation, what permissions might be required, or what happens when invoked. For a tool with zero annotation coverage, this is insufficient behavioral context.

    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 - a single sentence that directly states the tool's purpose. There's zero wasted language or unnecessary elaboration. 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.

    Completeness3/5

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

    Given that the tool has no parameters, 100% schema coverage, and an output schema exists, the description is minimally adequate. However, for a status-checking tool with no annotations, the description should ideally provide more context about what 'server status' means and what the output represents. The existence of an output schema helps, but the description itself lacks completeness for understanding the tool's behavior and results.

    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, and schema description coverage is 100%. With no parameters to document, the baseline for this dimension is 4. The description doesn't need to compensate for any parameter documentation gaps since there are none.

    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 tool's purpose: 'MCP 서버 상태를 확인한다' (Checks MCP server status). It uses a specific verb ('확인한다' - checks/verifies) and resource ('MCP 서버 상태' - MCP server status). However, it doesn't explicitly differentiate from its sibling tool 'list_supported_checks', which might have overlapping or related functionality.

    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?

    The description provides no guidance on when to use this tool versus alternatives. There's no mention of when this tool should be used, when it shouldn't, or how it differs from the sibling tool 'list_supported_checks'. The agent receives no contextual usage information beyond the basic purpose statement.

    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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