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solverio-pl

nip-checker-mcp

by solverio-pl
OverviewSchemaRelated ServersScoreDiscussions
JavaScript
Remote

Server Quality Checklist

67%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v1.0.4

  • Disambiguation5/5

    The two tools have completely distinct purposes: one checks the NIP itself against the VAT database, the other verifies a bank account against a NIP. There is no overlap or ambiguity in their functions.

    Naming Consistency5/5

    Both tool names follow the same verb_noun pattern: check_nip and check_nip_bank_account. The pattern is predictably extended with a qualifier, maintaining consistency.

    Tool Count4/5

    With only 2 tools, the server is minimal but well-scoped for its narrow purpose (NIP validation). It falls slightly below the typical 3-15 range, but the focus on two core operations makes the count appropriate.

    Completeness5/5

    The server covers the two essential operations for its domain: validating a NIP and verifying a bank account association. No obvious gaps exist for the stated purpose of a NIP checker.

  • Average 3.7/5 across 2 of 2 tools scored.

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

    • No community issues in the last 6 months
    • 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 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.

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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?

    With no annotations, the description carries the full burden. It mentions the data source (Ministry of Finance VAT taxpayer database) but does not disclose behavior such as read-only nature, response format, error cases, or potential rate limits. The description adds minimal behavioral context beyond the name.

    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, concise sentence that front-loads the action and key context. Every word earns its place, with no unnecessary filler.

    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 two well-documented parameters, and the description covers the core purpose. However, without an output schema or annotations, it does not explain what the check returns (e.g., registration status, boolean result), and it omits any reference to the optional date parameter, leaving some context gaps.

    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%, so the schema already documents both parameters. The description adds context for 'nip' as a Polish Tax Identification Number, but does not elaborate on the 'date' parameter or its default behavior, providing only marginal value beyond the schema.

    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?

    Clearly states the tool checks a Polish NIP against the Ministry of Finance VAT taxpayer database, using a specific verb and resource. This distinguishes it from the sibling tool check_nip_bank_account, which focuses on bank account verification.

    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?

    Provides no guidance on when to use this tool versus the sibling check_nip_bank_account, nor any scenarios for use. The description is purely functional and lacks context for selection.

    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 must carry the full behavioral burden. The verb 'verify' strongly implies a read-only operation, but the description does not explicitly state there are no side effects, permissions required, or other relevant behavioral details. It is not misleading, but minimal.

    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 clear sentence with no redundant words or repetition. It earns its place by stating exactly what the tool does.

    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?

    The tool is simple, with all parameters documented in the schema. The description fully captures the action and implies a boolean result. It lacks explicit mention of return format or any edge cases, but given the simplicity, it is nearly complete.

    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 (nip, date, bankAccount) already documented with types, patterns, and descriptions. The description adds no additional parameter-level semantics beyond reminding that the bank account is being verified against a NIP. 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 uses a specific verb ('verify') and resource ('bank account assigned to a specific NIP'), clearly distinguishing it from the sibling tool 'check_nip' which likely just checks NIP validity. The purpose is unambiguous and actionable.

    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 clearly states the tool's context (verifying bank account assignment to a NIP) but does not explicitly mention alternatives or exclusions. The sibling tool 'check_nip' provides implicit contrast, but no direct guidance is given in the description.

    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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