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imprvhub

Domain Availability Checker MCP

by imprvhub
OverviewSchemaRelated ServersScoreDiscussions
Python
Remote

Server Quality Checklist

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

  • Latest release: v1.0.0

  • Disambiguation5/5

    With only one tool, there is no possibility of confusion or overlap between tools. The single tool 'check_domain' has a clear, distinct purpose that cannot be mistaken for any other functionality.

    Naming Consistency5/5

    The naming is perfectly consistent as there is only one tool following a clear verb_noun pattern ('check_domain'). No mixed conventions or deviations exist to evaluate.

    Tool Count2/5

    A single tool is too few for a server that appears to handle domain availability checking, as this domain typically involves related operations like bulk checks, WHOIS lookups, or domain suggestion generation. The tool count feels thin and incomplete for the apparent scope.

    Completeness2/5

    The tool surface is severely incomplete for domain availability checking. While 'check_domain' covers basic availability queries, there are significant gaps such as no tools for WHOIS information, bulk domain checks, domain suggestion algorithms, or TLD-specific searches, which are common in this domain and will limit agent effectiveness.

  • Average 4.4/5 across 1 of 1 tools scored.

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

    • 0 of 1 community issues answered or closed in the last 6 months
    • 0 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 Mozilla Public License 2.0.

  • 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.

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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?

    With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes what the tool does (checks availability, returns results and alternatives) and provides usage examples that clarify behavior with different input formats. However, it doesn't mention rate limits, authentication needs, or error conditions.

    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 clear sections (purpose statement, usage examples, args, returns) and every sentence adds value. It's appropriately sized for a single-parameter tool with complex behavior, avoiding unnecessary verbosity while being comprehensive.

    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 the tool's moderate complexity (domain checking with TLD variations), no annotations, and an output schema present, the description provides excellent context. It explains the tool's behavior, parameter usage, and return format, making it complete enough for effective use without needing to reference the output schema for basic understanding.

    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?

    The schema description coverage is 0%, so the description must fully compensate. It successfully explains the single parameter's purpose ('Domain to check'), provides multiple usage examples showing how different inputs affect behavior, and clarifies the --domain flag context, adding significant value beyond the bare 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?

    The description clearly states the tool's purpose with a specific verb ('Check') and resource ('domain availability'), making it immediately understandable. It distinguishes this as a domain checking tool, which is unambiguous even without sibling tools for comparison.

    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 provides usage examples that imply when to use the tool (for domain availability checks), but it doesn't explicitly state when NOT to use it or mention alternatives. Without sibling tools, this is less critical, but the guidance remains implicit rather than explicit.

    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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