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dpmadsen

multimodels-mcp

by dpmadsen
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TypeScript
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Server Quality Checklist

67%
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  • Latest release: v0.4.1

  • Disambiguation5/5

    Os dois tools têm propósitos claramente distintos: list_models consulta modelos disponíveis, enquanto delegate_task envia tarefas para processamento. Não há sobreposição de funcionalidades.

    Naming Consistency5/5

    Ambos os nomes seguem o padrão snake_case e o formato verbo_substantivo (list_models, delegate_task), mantendo consistência total.

    Tool Count3/5

    Com apenas 2 tools, o servidor é enxuto demais para um ecossistema de delegação de tarefas. Embora cubra o fluxo básico, a quantidade fica na faixa considerada 'fina' pela escala.

    Completeness3/5

    Faltam operações como cancelamento de tarefas, verificação de status ou histórico de delegações. O design minimalista atende ao essencial, mas deixa lacunas que podem exigir workarounds.

  • Average 4.4/5 across 2 of 2 tools scored.

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

    • No community issues in the last 6 months
    • 19 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

  • Behavior4/5

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

    Annotations declare 'readOnlyHint': true, and the description adds that the tool provides exact ids and provider statuses, which aligns with read-only behavior. No contradictions, and additional context is provided beyond annotations.

    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, well-structured sentence that conveys all necessary information without any wasted words.

    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?

    For a simple list tool with no output schema, the description sufficiently explains what is returned (model IDs and provider statuses) and its relevance to the sibling tool, making it contextually complete.

    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 no parameters, so the description does not need to add parameter details. Schema coverage is trivially 100%, and the baseline for zero parameters is 4.

    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 lists 'modelos de IA habilitados para delegação' with specific details (id and status), and distinguishes itself from the sibling 'delegate_task' by providing the id needed for that tool.

    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 before 'delegate_task' by mentioning the id is for that tool, but it does not explicitly state when to use or not use this tool, nor does it provide alternative scenarios.

    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?

    Annotations mark readOnlyHint and openWorldHint, and the description confirms no side effects. It adds the behavioral note that the response comes from the delegated model and should be critically evaluated, providing useful context beyond annotations.

    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?

    Two sentences plus parameter context. Every sentence earns its place: purpose, usage hint, and caution. Front-loaded with the key action and result. No fluff.

    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 full schema coverage and no output schema, the description covers what the tool does, how to configure delegation, and potential pitfalls. It is sufficiently complete for an agent to use 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?

    Schema coverage is 100%, so baseline is 3. The description adds value by clarifying that 'task' must be self-contained, detailing 'effort' values per provider, and specifying when 'workdir' applies (codex, gemini). This goes beyond schema descriptions.

    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 clearly states the tool sends a task to another AI model and returns its response. It uses a specific verb ('Envia') and resource ('tarefa para outro modelo'), and the sibling 'list_models' is distinct, so purpose is unambiguous.

    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?

    Explicitly advises using list_models to find valid model IDs and cautions to critically evaluate the delegated model's response. However, it does not specify when not to use this tool, missing some exclusionary context.

    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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