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yoshinaga2015

kanpou-mcp

by yoshinaga2015
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JavaScript
Remote

Server Quality Checklist

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

  • Latest release: v1.0.0

  • Disambiguation2/5

    search_procurements already supports keyword and date filters, making get_procurements_by_date and search_by_keyword redundant specializations. Agents may struggle to decide which tool to use, as the boundaries are unclear and overlapping.

    Naming Consistency4/5

    All tool names follow a verb_noun pattern with consistent snake_case style. The slight inconsistency is that 'search_by_keyword' does not explicitly mention 'procurements' like the others, but it remains readable and predictable.

    Tool Count4/5

    Three tools is a reasonable count for a focused procurement search server. However, two tools are largely redundant subsets of the first, which suggests the count could be trimmed without losing functionality.

    Completeness3/5

    The server covers general search, date-based lookup, and keyword lookup, but lacks a way to fetch a specific procurement by ID or view detailed information. This is a notable gap for a procurement search domain.

  • Average 3.3/5 across 3 of 3 tools scored.

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

    • No community issues in the last 6 months
    • 0 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.

  • No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.

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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?

    There are no annotations, so the description must convey behavioral traits. It only states the basic search action without disclosing return format, pagination behavior, or any limitations. As a read operation, it does not explicitly confirm safety or side-effect-free behavior.

    Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

    Conciseness4/5

    Is the description appropriately sized, front-loaded, and free of redundancy?

    The description is a single, concise sentence with no redundancy. It is front-loaded with the key action, though it is too brief to provide extra context, which slightly reduces its usefulness.

    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 absence of annotations and output schema, the description is insufficiently complete. It does not mention how results are returned, any filtering limitations, or how it differs from sibling tools. The simple parameter set mitigates this slightly, but the description still lacks necessary context.

    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 100%, with both 'keyword' and 'count' already described in the input schema. The description adds no additional parameter meaning beyond what the schema provides, so a baseline of 3 is appropriate.

    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 identifies the action ('search') and the resource ('bidding information') and specifies the method ('by keyword'). However, it does not explicitly distinguish this tool from sibling 'search_procurements', which may overlap in 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?

    No guidance is provided on when to use this tool versus search_procurements or get_procurements_by_date. The description lacks any context for tool selection or exclusions.

    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 says the tool uses an external API and can filter, but does not disclose whether it's read-only, any rate limits, authentication requirements, pagination behavior, or result format. This is a significant transparency gap for a search tool.

    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, front-loaded sentence that states the core function and key filter capabilities without any redundant wording. It is appropriately sized for the information it conveys.

    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?

    Despite having 12 parameters and no output schema, the description is very brief. It does not mention the requirement that at least one of query, projectName, organizationName, or lgCode must be provided, nor does it explain how it relates to sibling tools. The rich schema descriptions compensate, but the description itself lacks contextual depth for such a complex 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 100%, with each parameter already having a detailed description (including required alternations and date formats). The tool description only generically mentions filter types (date, keyword, category, prefecture), adding no specific parameter semantics beyond what the schema already provides. Baseline 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?

    The description clearly states the tool searches for bid information using a specific API, with a clear verb '検索します' (search) and resource '入札情報' (bid information). It lists multiple filtering dimensions (date, keyword, category, prefecture), distinguishing it from the more narrow sibling tools get_procurements_by_date and search_by_keyword.

    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 multifaceted searches by mentioning multiple filter criteria, but does not explicitly state when to prefer this tool over the siblings or provide exclusions. It lacks explicit when-to-use or alternative guidance, so usage context is only implied.

    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 only states the basic operation and search field, with no mention of pagination, result limits, error behavior, or output format. This is minimal for a tool with zero annotation support.

    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 short sentences, efficiently conveying the core purpose and search field with no wasted words.

    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?

    Despite the simple nature of the tool, the description lacks any mention of return values, which is critical since no output schema is provided. With no annotations and no output schema, the agent is left without information about what the tool returns or expects.

    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 schema already fully covers both parameters, but the description adds meaning by specifying that the date parameter refers to the announcement date, which is not explicitly stated in the schema. This supplementary context helps the agent understand the parameter semantics better.

    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 procurement information for a specified date, and specifically by announcement date. This distinguishes it from sibling tools like search_by_keyword, which are likely keyword-based.

    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 date-based searches but provides no explicit guidance on when to use this tool versus the sibling tools. It does not mention alternatives or 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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