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kmprograms

YouTube Transcripts MCP Server

by kmprograms
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Server Quality Checklist

58%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v0.1.0

  • Disambiguation5/5

    The two tools serve clearly distinct purposes: one fetches full transcript content, the other lists available transcripts without content. No overlap.

    Naming Consistency5/5

    Both tools follow a consistent verb_noun snake_case pattern: get_transcript and list_transcripts.

    Tool Count4/5

    Two tools is minimal but appropriate for a focused read-only transcript service. Could add more but not needed.

    Completeness5/5

    The tool set covers the essential operations: listing available transcripts and retrieving one. No gaps for the stated purpose.

  • Average 4/5 across 2 of 2 tools scored.

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

    • No community issues in the last 6 months
    • 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

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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?

    With no annotations, the description provides some behavioral details: returns text and metadata (language, fragment count). But it does not disclose error cases, such as when no transcript is available or language preference fails.

    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 four concise sentences in Polish, each adding unique value: purpose, argument format, optional parameter, return info. No wasted words, front-loaded with core function.

    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?

    The tool is low complexity (2 params, 1 required) and has an output schema. The description covers input, output, and purpose. It does not mention error handling or when to use, but overall is sufficiently complete for most use cases.

    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 has 0% description coverage, so the description compensates by explaining that 'video' accepts URL or 11-char ID, and 'languages' is a list of language codes in preference order. This adds significant meaning beyond schema structure.

    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?

    Description clearly states it downloads a YouTube video transcript, including how to specify the video (URL or 11-char ID) and optional languages. However, it does not explicitly differentiate from sibling 'list_transcripts'.

    Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

    Usage Guidelines2/5

    Does the description explain when to use this tool, when not to, or what alternatives exist?

    No guidance on when to use this tool versus the sibling 'list_transcripts'. The description lacks any when-to-use or when-not-to-use advice.

    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?

    No annotations are provided, but the description clearly states that the tool does not fetch transcript content, implying a read-only operation. This adequately discloses the tool's behavior for an agent.

    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 consists of two clear, front-loaded sentences without any unnecessary text. Every sentence provides essential information.

    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 the simplicity of the tool and the presence of an output schema, the description covers purpose, usage, and behavior. However, it lacks parameter clarification, which is a minor gap.

    Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

    Parameters2/5

    Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

    The input schema has 0% description coverage for the 'video' parameter, and the tool description does not explain what format or value is expected (e.g., video ID or URL). This leaves ambiguity for the agent.

    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 it returns a list of transcripts for a YouTube video without fetching content. It clearly distinguishes from the sibling tool 'get_transcript' by noting it does not retrieve the transcript content.

    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 directly says it is useful when you want to first check available languages before fetching a transcript. This provides clear guidance on when to use this tool versus its sibling.

    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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