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Denisijcu

MCP GraphQL Server Multi-Fuente

by Denisijcu

graphql_batch

Execute multiple GraphQL queries in one call across CSV, Google Sheets, SQL, NoSQL, and Oracle sources, with optional variables per query.

Instructions

Ejecuta múltiples consultas GraphQL en una sola llamada

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queriesYesLista de consultas GraphQL
variablesNoLista de variables

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.1/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full behavioral burden, yet it discloses nothing about execution semantics: ordering of results, whether queries run serially or in parallel, how partial failures or per-query errors are surfaced, or whether authorization applies per query. For a batch execution tool with zero annotation coverage this is a substantial gap.

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?

A single short sentence with zero waste and the core action front-loaded. It is efficient, though its brevity is also what leaves the behavioral and usage gaps unaddressed.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

No output schema and no annotations, so the description is the only source of behavioral detail — and it omits result shape, error semantics, and ordering. For a batch tool whose callers must reason about multiple sequential inputs, this is not complete enough.

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% ('Lista de consultas GraphQL', 'Lista de variables'), so the schema already defines both parameters. The description adds no positional/index correspondence between the queries array and the variables array, so it does not improve on the schema — baseline 3 applies.

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?

Specific verb+resource: 'Ejecuta múltiples consultas GraphQL en una sola llamada' clearly states batch execution of GraphQL queries, and the word 'múltiples' implicitly contrasts with the single-query sibling graphql_query. It stops short of naming graphql_query or graphql_mutation explicitly, so the differentiation is left to inference.

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 phrase 'en una sola llamada' implies the tool is for batching many queries, which hints at when it beats graphql_query. But there is no explicit when-to-use/when-not guidance, no mention of graphql_mutation as the alternative for writes, and no stated limits or batching conditions.

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