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Andres2009

facturas-mcp

by Andres2009
OverviewSchemaRelated ServersScoreDiscussions
TypeScript
Hybrid

Server Quality Checklist

58%
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  • Latest release: v1.0.0

  • Disambiguation5/5

    The two tools have clearly distinct roles: one is for inspecting the table schema, the other for executing read-only SQL queries against the table. There is no overlap or ambiguity about which to call.

    Naming Consistency5/5

    Both tool names follow the same lowercase snake_case verb_object pattern in Spanish: listar_columnas_facturas and consultar_facturas. The naming is predictable and aligns with each tool's function.

    Tool Count4/5

    With only two tools, the server is minimal, but the scope is intentionally narrow: schema discovery plus SQL querying of a single invoices table. This is slightly below the typical 3-15 tool range but reasonable and well-scoped for its purpose.

    Completeness5/5

    For a read-only query server over DWH.facturas, the surface is complete: agents can discover the schema and then run arbitrary SELECT queries to answer business questions. No obvious additional operations are needed for the stated purpose.

  • Average 4.5/5 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

  • Behavior4/5

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

    No hay anotaciones, por lo que la descripción asume la responsabilidad de informar el comportamiento. Revela que solo es una operación de lectura, que acepta únicamente SELECT y que cualquier otra consulta será rechazada. Esto es un contexto conductual valioso, aunque no detalla formato de respuesta ni límites de ejecución.

    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?

    Tres oraciones con información esencial y sin relleno. La restricción crítica (solo SELECT) está al frente, y la referencia a la herramienta hermana es breve y pertinente.

    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?

    Para una herramienta de un solo parámetro, la descripción cubre el propósito, las restricciones de uso y el paso a seguir si falta conocimiento de columnas. No hay anotaciones ni esquema de salida, pero el contexto entregado es suficiente para que el agente invoque la herramienta correctamente.

    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?

    El esquema cubre el 100% del parámetro sql y ya incluye descripción y ejemplo, así que la descripción no necesita añadir mucho. La descripción refuerza que el SQL debe ser SELECT y contra DWH.facturas, pero no agrega detalles semánticos nuevos más allá del esquema.

    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?

    La descripción usa un verbo específico ('Ejecuta una consulta SQL de solo lectura') y un recurso concreto ('tabla DWH.facturas'), dejando claro qué hace la herramienta. Además, la diferencia de la herramienta hermana listar_columnas_facturas al indicar que ésta es para consultar datos, no para conocer columnas.

    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?

    Indica explícitamente cuándo usarla: para responder preguntas de negocio que requieran datos de DWH.facturas. También establece exclusions ('solo se permite SELECT... cualquier otra cosa se rechaza') y recomienda usar listar_columnas_facturas cuando no se conocen las columnas, lo que orienta claramente al agente.

    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 provided, the description carries the burden of disclosing behavior. It clearly indicates a read-only metadata operation returning column names and types, and its wording implies no side effects on the table. It doesn't detail output formatting, but that is a minor gap for a schema-listing 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 two short sentences with no filler. The primary function is stated first, followed by a concise usage directive. Every sentence earns its place.

    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 zero-parameter schema-inspection tool with no output schema, the description is complete: it states the return content, the target table, and the appropriate invocation point relative to querying. An agent has enough information to use the 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?

    The tool has zero parameters, so the baseline of 4 applies. The description adds useful context about which table is inspected and when the tool should be used, even though there are no parameters to explain.

    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 states a specific verb and resource: it returns the name and type of each column in DWH.facturas. This clearly separates the tool from the sibling consultar_facturas, which is presumably for querying data rather than inspecting schema.

    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 says to use this tool first, before writing a query, when the table schema is unknown. It gives clear situational guidance, though it doesn't explicitly name the alternative tool or state when not to use it.

    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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