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prazedotid

UUID MCP Provider

by prazedotid
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TypeScript
Hybrid

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 ambiguity or overlap between tools. The tool has a single, clearly defined purpose of generating UUID v7s, making it impossible for an agent to misselect among alternatives.

    Naming Consistency5/5

    The tool name 'generateUuid' follows a clear verb_noun pattern (generate + Uuid), and since there is only one tool, there is no inconsistency to evaluate. The naming is straightforward and predictable for its singular function.

    Tool Count2/5

    A single tool is too few for most practical server purposes, as it offers minimal functionality and lacks related operations. While UUID generation is a narrow domain, typical MCP servers benefit from more tools (e.g., 3-15) to cover broader workflows, making this feel thin and limited in scope.

    Completeness3/5

    The tool covers the core function of generating UUID v7s, but there are notable gaps in the domain. For example, it lacks tools for validating UUIDs, generating other UUID versions (e.g., v4), or handling UUID-related operations like parsing or conversion, which limits agent capabilities in broader UUID management tasks.

  • Average 3.5/5 across 1 of 1 tools scored.

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

    • No community issues in the last 6 months
    • 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 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

  • Behavior3/5

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

    No annotations are provided, so the description carries the full burden. It discloses that the tool generates UUID v7s (timestamp-based) and allows multiple generations via a count parameter, but it does not cover behavioral traits like rate limits, error handling, or output format. This adds basic context but leaves gaps in transparency.

    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 two sentences, front-loaded with the core purpose and followed by parameter guidance. Every sentence earns its place without waste, making it efficient and well-structured for quick comprehension.

    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?

    Given the tool's low complexity (one optional parameter, no output schema, no annotations), the description is somewhat complete but lacks details on output format or behavioral constraints. It covers the basic operation but could be more informative for an agent to use the tool effectively without additional context.

    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?

    The schema description coverage is 100%, with the parameter 'count' fully documented in the input schema. The description adds minimal value by mentioning 'Specify `count` to get multiple,' which reinforces but does not expand beyond the schema. With high coverage, the baseline is 3, as the description does not significantly enhance parameter understanding.

    Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

    Purpose4/5

    Does the description clearly state what the tool does and how it differs from similar tools?

    The description clearly states the tool's purpose: 'Generate one or more UUID v7s (timestamp-based).' It specifies the verb ('Generate'), resource ('UUID v7s'), and type ('timestamp-based'), but since there are no sibling tools, it cannot differentiate from alternatives. This makes it clear but not maximally specific.

    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 implies usage by stating 'Specify `count` to get multiple,' which suggests when to use the optional parameter. However, it lacks explicit guidance on when to use this tool versus alternatives or any exclusions, as there are no siblings. This provides some context but is not comprehensive.

    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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