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lmaniraruta

license-verify-mcp

by lmaniraruta
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Server Quality Checklist

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

  • Latest release: v0.1.1

  • Disambiguation5/5

    The two tools have clearly distinct purposes: one lists supported jurisdictions, the other verifies a contractor's license. No overlap in functionality, making selection unambiguous.

    Naming Consistency5/5

    Both tools follow a consistent verb_noun pattern: list_supported_jurisdictions and verify_license. The naming is clear and predictable.

    Tool Count3/5

    With only 2 tools, the server feels minimal. While the scope is narrow, a typical license verification server might include additional tools like get_license_details or search_business_by_name.

    Completeness4/5

    The tool set covers the core workflow: listing available jurisdictions and verifying a license. Minor gaps exist, such as no tool to retrieve a specific jurisdiction's details or support for other license types.

  • Average 4.7/5 across 2 of 2 tools scored.

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

    • No community issues in the last 6 months
    • 12 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

  • Behavior4/5

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

    No annotations are provided, so the description carries full burden. It discloses that the tool returns an array with fields (code, full name, source, status) and mentions 'live or coming_soon' status, which gives clear behavioral insight. There is no contradiction.

    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 concise, using a single line for purpose followed by three bullet points for usage guidelines and one sentence for return value. Every part is essential and front-loaded.

    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 no output schema, the description adequately describes the return structure. With no inputs, it fully covers behavioral expectations. The tool is simple, and the description is complete.

    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?

    Input schema has zero parameters, and schema coverage is trivially 100%. The description does not need to add parameter semantics, and it correctly omits any. Baseline for 0 parameters is 4.

    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 explicitly states the tool lists supported US states with data source and availability. It uses a specific verb ('list') and resource ('supported jurisdictions'), and distinguishes from the sibling tool 'verify_license' by implying this tool is for checking support before calling the other.

    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 when to call the tool: to check state support, display options, or get data source URL. It provides explicit context but does not include when-not-to-use or alternatives, though the use cases are well-defined.

    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?

    With no annotations, the description fully carries behavioral disclosure. It states the tool is read-only, returns structured JSON with status enum, details on bond/insurance, and explains the matches array for ambiguous business names. This is comprehensive.

    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 well-structured with bullet points (hyphens in text), front-loaded with the main purpose, and every sentence adds unique value. It is concise but covers all necessary aspects without redundancy.

    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 no output schema, the description adequately explains return values (structured JSON with status, dates, bond info, raw source, and matches array). It covers jurisdiction support and input requirements. Minor deduction for not detailing every possible field, but sufficient for agent use.

    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?

    Schema coverage is 100%, so baseline is 3. The description adds value beyond schema: it explains preference for license_number, case-insensitive partial matching for business_name, and mentions that business_name may return multiple results. This extra guidance justifies a 4.

    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's purpose: verifying a contractor's license/registration status before awarding work. It specifies the verb 'verify', the resource 'license/registration', and includes context about when to use it. It also distinguishes from the sibling tool list_supported_jurisdictions.

    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?

    The description provides explicit when-to-use scenarios (confirm licensing, check status, look up by number/name) and when-not-to (calling list_supported_jurisdictions first). It also clarifies behaviors like partial vs exact matching and multiple matches.

    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 the MCP server is working as expected.
  • Confirm that there are no obvious security issues.
  • Evaluate tool definition quality.

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