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matematicsolutions

mcp-krs

by matematicsolutions
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JavaScript
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Server Quality Checklist

75%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v1.1.0

  • Disambiguation5/5

    Each tool targets a distinct use case: get_board for quick board composition summary, get_entity for current full entity data, and get_entity_full for historical records. There is no ambiguity or overlap between them.

    Naming Consistency5/5

    All tool names follow a consistent get_ prefix pattern with snake_case (get_board, get_entity, get_entity_full), making the naming predictable and easy to understand.

    Tool Count5/5

    Three tools is an appropriate number for a specialized KRS data retrieval server. Each tool serves a distinct purpose covering the main query needs without being excessive or too sparse.

    Completeness4/5

    The tools cover the main read operations for KRS entities (current data, full history, board summary). However, a search tool by name or NIP is missing, which would be a natural complement for a complete data retrieval surface.

  • Average 4.3/5 across 3 of 3 tools scored.

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

    • No community issues in the last 6 months
    • 10 commits in the last 12 weeks
    • Last stable release on
    • 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.

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

    Tip: use the "Try in Browser" feature on the server page to seed initial usage.

  • This repository includes a glama.json configuration file.

  • If you are the author, simply .

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    {
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}

    Then . Browse examples.

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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

  • Behavior4/5

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

    Annotations already mark the tool as read-only and idempotent. Description adds behavioral details like automatic zero-padding of KRS to 10 digits and inclusion of a URL to the KRS search engine.

    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?

    Description is a single paragraph that front-loads the main purpose. It is informative but slightly verbose; could be tightened.

    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?

    Despite no output schema, description comprehensively lists returned fields, including URL. For a read-only tool with two parameters, this provides complete context for use.

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

    Parameters5/5

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

    Schema covers all parameters, but description adds behavior for 'krs' (zero-padding) and clarifies enum values for 'rejestr' (default and alternatives).

    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 retrieves a current extract from the National Court Register by KRS number, listing specific data returned. It uses a specific verb and resource, distinguishing it from siblings like get_board and get_entity_full by focusing on a single entity's full details.

    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 on when to use this tool versus alternatives. No mention of prerequisites or context for selection.

    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 provide readOnlyHint=true and destructiveHint=false. The description adds behavioral context by stating it is based on a current extract and is faster. No contradictions 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, no wasted words. Front-loaded with the core purpose and key differentiator.

    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 simple input schema and presence of annotations, the description adequately covers what the tool returns, its data source, and performance advantage. No output schema needed explanation.

    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 covers 100% of parameters with descriptions. The description does not add additional meaning to parameters beyond what the schema provides, 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?

    The description clearly states this tool returns board composition, representation method, and proxies. It distinguishes itself from get_entity by being faster and more focused, and the name 'get_board' aligns with the described scope.

    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?

    Explicitly says to use this when you need 'who represents X' and that it's faster than get_entity. However, it does not mention when not to use it or address the sibling get_entity_full, leaving some gaps.

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

  • Behavior5/5

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

    Description discloses behavioral traits beyond annotations: returns history including each change, deletion, previous management boards, and larger response. Annotations already indicate readOnlyHint=true, destructiveHint=false, idempotentHint=true, and description aligns and adds detail.

    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, no fluff, front-loaded with purpose and key differentiator. Every sentence adds value.

    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 tool with good annotations and no output schema, description covers what the tool returns and when to use it. Could mention output format explicitly but not required given clarity. Slight room for improvement.

    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%, so baseline is 3. Description does not add additional parameter insights beyond what is already in schema (krs number, rejestr with enum). No contradiction, but no extra value.

    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 'Pobiera' (retrieves) and resource 'ODPIS PELNY z KRS' with history. It distinguishes from siblings by specifying it provides full history of changes, not just current state, which contrasts with likely simpler tools like get_entity and get_board.

    Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

    Usage Guidelines5/5

    Does the description explain when to use this tool, when not to, or what alternatives exist?

    Explicitly tells when to use: 'uzywaj kiedy potrzebujesz historii zmian, nie tylko stanu aktualnego' (use when you need history of changes, not just current state). This implies alternative for current state, providing clear context.

    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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  • Confirm that there are no obvious security issues.
  • Evaluate tool definition quality.

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