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rocnubie

videotoaudioconverter-mcp

by rocnubie
OverviewSchemaRelated ServersScoreDiscussions
JavaScript
Remote

Server Quality Checklist

67%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v0.1.0

  • Disambiguation5/5

    The two tools are clearly distinct: one provides local setup instructions, the other provides official links. There is no overlap in purpose, so an agent can easily choose the correct tool.

    Naming Consistency5/5

    Both tools follow a consistent get_<noun> pattern, with descriptive nouns (local_setup, official_links). The naming is predictable and uniform.

    Tool Count3/5

    With only two tools, the server feels minimal and thin for its name. However, if the server's scope is solely to provide setup and link information, the count is not entirely unreasonable, though it is borderline.

    Completeness1/5

    The server claims to be a 'Video to Audio Converter' but provides no conversion-related functionality. There are no tools for converting, managing files, or handling formats—only informational utilities. This is a severe gap relative to the apparent domain.

  • 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
    • No commit activity data available
    • 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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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?

    With no annotations provided, the description carries the full burden of behavioral disclosure. It merely restates the tool's function without noting any side effects, return format, or prerequisites. For a simple getter, more transparency about the nature of the returned guidance would be expected.

    Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

    Conciseness4/5

    Is the description appropriately sized, front-loaded, and free of redundancy?

    The description is a single concise sentence that delivers the core message. However, the parenthetical '(Video to Audio Converter)' is ambiguous and adds complexity without clear value, slightly reducing structure quality.

    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 (0 params, no output schema), the description adequately states the purpose but leaves gaps about the exact content of the local-setup guidance and how it differs from the sibling tool. It is sufficient for basic invocation but lacks full context.

    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?

    The tool has zero parameters, so the baseline score is 4. The description does not need to explain parameter semantics, and the empty schema aligns perfectly with the no-parameter requirement.

    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 'canonical local-setup guidance' for running the AI workflow on-device, using a specific verb and resource. It distinguishes itself from the sibling tool get_official_links by focusing on local setup rather than official links.

    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 the tool is for obtaining local setup guidance, but it does not explicitly state when to use it versus alternatives like get_official_links. There is no exclusion or when-not guidance, so the usage context is implied rather than explicit.

    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?

    No annotations are provided, so the description carries the disclosure burden. It clearly states the tool returns a canonical list, implying a read-only operation and disclosing that some links may only be present 'when available'. For a simple getter with no side effects, this is adequate behavioral transparency, though it does not detail return structure or error behavior.

    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, front-loaded sentence. Every word contributes: 'canonical' clarifies the authoritative nature, the product name disambiguates, and 'when available' adds a necessary caveat. No redundancy.

    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?

    Given the tool has no parameters, no output schema, and no annotations, the description alone must define the tool's behavior. It fully specifies that the output is a list of official links for the product, including the categories of links. This is sufficient context for an agent to select and invoke this tool correctly.

    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?

    There are zero parameters, so per the rubric the baseline is 4. The description adds value by explaining the tool's output context, but there are no parameter semantics to elaborate on.

    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 uses a specific verb 'Return' and identifies the exact resource: the canonical list of official links for Video to Audio Converter. It enumerates the types of links (website, support, docs) and adds the 'when available' caveat, making the tool's purpose unmistakable and distinct from the sibling get_local_setup.

    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 the tool should be used when official links are needed, but it does not explicitly state when to prefer this over get_local_setup or provide exclusions. The guidance is present but only through inference from the tool name and resource description.

    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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