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shopify-chatgpt-ads-mcp

shopify-chatgpt-ads-mcp

by Avada-AI
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
Local

Conversion event settings

list_conversion_event_settings
Read-only

List available conversion event settings to see which events and data sources count as conversions, then choose an active standard setting ID for a conversions-objective campaign.

Instructions

Which events count as conversions (e.g. order_created) and on which data source. A conversions-objective campaign needs one active standard setting id from here.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "list_conversion_event_settings"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

A3.9/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false and openWorldHint=true, so the safety profile is covered. The description adds a behavioral detail beyond that — that the relevant entries are 'active standard' settings — but says nothing about return shape, ordering, or whether inactive/custom settings also appear.

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 short sentences with zero padding, and the meaning of the returned data is stated before the downstream use case. Every clause carries information.

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?

For a no-parameter, no-output-schema list tool this covers what it is and why an agent would call it. The main residual gap is that the 'setting id' an agent is told to pick up is named but not characterized (no field name, no mention of other fields returned).

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 takes zero parameters, so there is nothing to disambiguate and the baseline of 4 applies. The description correctly implies no required input is needed to fetch the settings.

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?

Names the resource precisely: conversion event settings, defined as which events count as conversions and which data source they belong to. An agent can distinguish this from a recent-events list by the 'settings' framing, though the description never explicitly contrasts them.

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?

Supplies a concrete selection condition: you need this when setting up a conversions-objective campaign, which requires one active standard setting id. It does not state any exclusion or when-not-to-call condition, so it falls short of full routing guidance.

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

Deploy Server

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