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Soboljem

transcribe-mcp

by Soboljem
OverviewSchemaRelated ServersScoreDiscussions
JavaScript
Remote

Server Quality Checklist

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

  • Latest release: v0.1.2

  • Disambiguation5/5

    Each tool serves a completely distinct role: transcribe_url handles audio-to-text, find_dead_air post-processes timings to find silence, and shop_info provides pricing metadata. There is zero overlap in purpose.

    Naming Consistency4/5

    Tool names follow a clear verb_noun pattern (transcribe_url, find_dead_air, shop_info) with snake_case. shop_info deviates slightly from the domain-action style of the others, but it is still predictable and readable.

    Tool Count5/5

    Three tools is perfectly scoped for this server: a core action (transcribe), a derived analysis (find_dead_air), and informational helper (shop_info). No tool feels extraneous, and the count matches the narrow purpose well.

    Completeness4/5

    The tool surface covers the key transcription workflow and provides a helpful cost info tool. An obvious gap is the lack of an update or delete operation for transcripts, but for a consumption-oriented service this is reasonable. The surface feels complete for its intended use.

  • Average 4.3/5 across 3 of 3 tools scored.

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

    • No community issues in the last 6 months
    • 5 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

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  • 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

  • Behavior4/5

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

    With no annotations, the description carries the full burden. It discloses the per-call cost, that 'the expensive half is not redone' (implying caching or reuse), and that it returns spans and savings estimates. This is transparent for a read‑only analysis tool, though limits like max input size or error handling are not mentioned.

    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 delivers core purpose in the first sentence, then adds essential usage and cost info in a second sentence. No redundant words; every sentence earns its place. It is front‑loaded and efficient.

    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 has 3 optional parameters and no output schema. The description explains the input options (VTT or segments), the pipeline from transcribe_url, and the nature of the output (spans and saving estimate). It lacks a precise specification of the return format, but the description is sufficient for an agent to invoke the tool correctly.

    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 description coverage is 100%, so baseline is 3. The description adds context about using segments from transcribe_url and the cost, but does not significantly expand on what the parameters mean beyond the schema. The value comes from pipeline guidance rather than parameter detail.

    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 returns 'the spans of dead air and how much of the runtime cutting them would save,' which is a specific verb+resource. It distinguishes itself from the sibling 'transcribe_url' by focusing on silence detection rather than transcription.

    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 explicitly tells the agent to 'feed it the segments transcribe_url returns,' establishing a clear pipeline. It also highlights the cost advantage ($0.002 vs. transcription cost). However, it does not explicitly state when not to use this tool (e.g., if no subtitles or timings are available).

    Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

  • Behavior3/5

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

    The description states the tool is free, which is a key behavioral trait. However, with no annotations, it doesn't disclose auth requirements, side effects, or whether results are cached or dynamic. This partial transparency is adequate for a simple cost-checking tool.

    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 a single sentence front-loaded with 'Free.' It wastes no words while conveying purpose, output, and usage context. Every word earns its place.

    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 zero parameters and no output schema, the description sufficiently covers what the tool returns and when to use it. It lacks details about response format or authentication, but the low complexity makes it complete enough for a simple info 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?

    With zero parameters, the input schema requires no explanation. The description adds value by specifying what the tool returns, which is not parameter semantics but does inform the agent's decision to call it.

    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 returns specific information (prices, size limit, chain, payment) and positions it as a free decision support tool before using paid tools. This distinguishes it from siblings transcribe_url and find_dead_air, which have different purposes.

    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 explicitly tells the agent to use this tool before calling paid tools to decide if they are needed. While it doesn't list exclusions or alternative tools, the context of preventing unnecessary paid calls is clear and actionable.

    Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

  • Behavior4/5

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

    With no annotations, the description carries full burden. It discloses cost, payment method, file size limit, and refusal policy for oversized files. It also describes output behavior (per-segment timings and language detection). Missing details on error handling for unreachable URLs but overall provides key behavioral context.

    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?

    Three sentences, front-loaded with purpose, each sentence adding non-redundant information (purpose, cost, size limit). Concise without missing critical details.

    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?

    For a single-parameter tool with no output schema and no annotations, the description covers purpose, cost, size limit, and output shape (timings, language). It is sufficient for an agent to decide to invoke, though more detail on output format would increase completeness.

    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% with a basic param description. The tool description adds value beyond the schema: constraints (public reachable, <800KB), cost, and output details. This helps an agent understand the parameter's context and limits.

    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 transcribes audio/video from a URL into text with per-segment timings and detected language. The verb 'transcribe' and resource 'audio or video from a URL' are specific and distinct from unrelated sibling tools.

    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 tells when to use: for public URLs needing transcription with timings and language detection. It provides important constraints (file <800KB, cost $0.05, USDC payment). However, it does not explicitly state when to avoid the tool or suggest alternatives, though siblings are unrelated.

    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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