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Run a read-only AxonHub GraphQL query

axonhub_graphql_query

Execute custom read-only GraphQL queries against AxonHub admin API. Retrieve projects, channels, models, requests, and usage stats while mutations, subscriptions, and sensitive fields are blocked.

Instructions

Run a custom query against /admin/graphql. Mutations and subscriptions are rejected; sensitive fields are redacted.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes
projectIdNoAxonHub project ID. Uses AXONHUB_PROJECT_ID when omitted.
variablesNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.9/5.0
Behavior4/5

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

With no annotations provided, the description carries the full transparency burden. It discloses key behavioral traits: the operation is read-only, mutations and subscriptions are rejected, and sensitive fields are redacted. It could go further by mentioning error behavior or response shape, but the most important safety-related behaviors are explicitly stated.

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 sentences, front-loads the primary action and target, and then adds the essential constraints. Every word earns its place with no filler or repetition of schema details.

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?

The tool is a flexible GraphQL executor with no output schema, so the description should ideally point toward how to learn valid queries, such as using the sibling axonhub_schema tool. It also omits the response format. For a well-known GraphQL pattern this is adequate, but for an agent selecting among siblings it leaves nontrivial gaps.

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 only 33% (only projectId is described), so the description must compensate. It adds useful meaning by clarifying that the query must be a read-only GraphQL query and by naming the endpoint, but it does not explain the variables object or the expected shape of the query string beyond 'custom query'. This is partial compensation, not full.

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 action ('Run a custom query'), the specific resource ('/admin/graphql'), and the read-only nature of the operation. It also adds behavioral constraints ('Mutations and subscriptions are rejected; sensitive fields are redacted') that make the tool's purpose unambiguous and distinct from the sibling data-listing tools.

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 custom GraphQL queries and explicitly says mutations/subscriptions are not allowed, which tells the agent when not to use it for writes. However, it never mentions alternatives or directs the agent to sibling tools like axonhub_schema for discovering valid queries, so the 'when to use vs alternatives' guidance is left mostly implicit.

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