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xbhog

namebeta-mcp

by xbhog

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 a single tool, there is no possibility of overlap or confusion. The tool's purpose is unique by default.

    Naming Consistency5/5

    The single tool uses a clear verb_noun pattern (lookup_domain), establishing a consistent convention even with an isolated example.

    Tool Count2/5

    A single tool is minimal for a server; while the tool is non-trivial and well-scoped, the server feels incomplete for broad use cases like domain search or management.

    Completeness4/5

    For a pure lookup service, the tool covers the core workflow well (search, availability, registration details). However, adjacent operations like domain suggestions or WHOIS history are absent, leaving minor gaps.

  • Average 4.7/5 across 1 of 1 tools scored.

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

    • No community issues in the last 6 months
    • 1 commit 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.

  • 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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  • If you are the author, simply .

    If the server belongs to an organization, first add glama.json to the root of your repository:

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

    Then . Browse examples.

  • Add related servers to improve discoverability.

How to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

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, the description carries the behavioral disclosure burden. It discloses key behaviors: spaces are stripped, .com is used as primary unless a TLD is present, already-domain values are used as-is, and the response always includes specific availability data. It does not mention rate limits or error conditions, but the core behavior for a read-only lookup is well covered.

    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 compact, purpose-first, and every sentence adds value: purpose, guaranteed return fields, invocation trigger with examples, and normalization rules. It contains no fluff or repetition of schema details.

    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?

    Since there is no output schema, the description explicitly lists what the tool always returns, including registration/expiry dates and available domains. It also explains how user input is preprocessed and how defaults are chosen, covering all the important runtime behavior an agent would need to call and interpret the tool.

    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 a baseline of 3 applies; the description adds meaningful context on top: it explains how the keyword gets normalized (spaces stripped) and when tld is applied, clarifying real-button behavior beyond the schema fields. The tld behavior is also connected to the 'already a domain' rule, which helps the agent choose correct values.

    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 states the exact operation (querying NameBeta's full suffix list for a keyword) and defines the expected outputs: total suffixes, registered vs. available counts, taken domains with dates, and the complete available list. It is specific and does not merely restate the tool name.

    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?

    It explicitly says 'Call this whenever the user types a keyword, brand, product name, or domain' and gives concrete examples ('google flow video', 'naruto character generator'). Even without siblings, the trigger condition and input scope are unambiguous.

    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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Glama performs regular codebase and documentation scans to:

  • 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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