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NarglesCS

GraphMCP

by NarglesCS

graphql_query

Execute read-only GraphQL queries to retrieve specific fields and get data or error responses. Mutations are excluded.

Instructions

Execute a read-only GraphQL query and return {"data", "errors"}.

Select only the fields you need. Example:

query($role: Role) {
  users(role: $role) { name posts(limit: 2) { title } }
}

with variables {"role": "ADMIN"}. Mutations are rejected here.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes
variablesNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

With no annotations provided, the description discloses critical behavioral details: it is read-only, returns both data and errors, and explicitly rejects mutations. It also gives a concrete example of query and variables, adding useful context. It could mention auth requirements or rate limits, but for a simple read-only query tool, this is above average.

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 concise and well-structured: a one-sentence purpose, a clear guidance to select only needed fields, and a single example that covers both parameters. No redundant or filler content.

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?

Despite having no annotations, the description provides all necessary context for an agent to invoke the tool correctly: purpose, read-only guarantee, mutation rejection, parameter format, and return shape. The sibling tools are distinguishable, and the output schema is mentioned via the return {'data', 'errors'}. It is complete for a tool of this complexity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has zero description coverage, but the description fully compensates by providing a complete example showing both the 'query' string and 'variables' object with a role variable. This demonstrates the exact format for both parameters and their relationship, adding significant meaning beyond the schema.

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 'Execute a read-only GraphQL query' with a specific verb and resource, and explicitly distinguishes it from the sibling graphql_mutate by noting 'Mutations are rejected here.' This leaves no ambiguity about the tool's function.

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?

It clearly indicates read-only usage and rejects mutations, which tells the agent when not to use this tool. However, it does not explicitly name alternatives like graphql_schema or graphql_validate, though the 'read-only' and 'mutations rejected' framing implies the correct 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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