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dkasaj

Tubist MCP Server

by dkasaj
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Server Quality Checklist

67%
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  • Latest release: v1.0.0

  • Disambiguation5/5

    With only one tool, there is no possibility for confusion. The tool 'play' clearly has a distinct purpose.

    Naming Consistency4/5

    The single tool name 'play' is a verb that describes its action well, but with only one tool, consistency cannot be fully assessed; it is reasonable.

    Tool Count2/5

    A single tool for a YouTube video server is too limited. Typical functionality would include search, listing, or details, making this feel incomplete.

    Completeness2/5

    The server only offers a 'play' action, lacking any way to discover or manage videos, which leaves obvious gaps for any practical use.

  • Average 3.7/5 across 1 of 1 tools scored.

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

    • No community issues in the last 6 months
    • 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 status not available

  • This repository is licensed under MIT License.

  • This repository includes a README.md file.

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    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

  • Behavior2/5

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

    No annotations are provided, so the description bears full responsibility for behavioral disclosure. It only states 'Play a YouTube video' without detailing side effects, such as whether it replaces a currently playing video, requires specific permissions, or affects playback state.

    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?

    Description is a single, concise sentence containing no redundant information. Every word is necessary and front-loaded with the core action.

    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 simplicity (one parameter, no output schema, no siblings), the description is adequate but minimal. It could be enhanced with details like playback behavior or error conditions, but it meets a minimum viable standard.

    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% with a single parameter 'url' that includes a description and example. The tool description adds no additional parameter context beyond what the schema already provides. Baseline score of 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?

    Description uses specific verb 'Play' and identifies resource 'YouTube video' within context 'Tubist', clearly stating the tool's action and scope. With no sibling tools, differentiation is not required.

    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 implies when to use the tool (to play a YouTube video in Tubist). However, it provides no explicit guidance on when not to use it or alternatives, which is acceptable given the absence of sibling tools.

    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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  • Evaluate tool definition quality.

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