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shopify-chatgpt-ads-mcp

shopify-chatgpt-ads-mcp

by Avada-AI
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
Local

Get ad

get_ad
Read-only

Retrieve a specific ad by ID to inspect its creative, review status, and serving issues.

Instructions

One ad with creative, review_status and serving issues.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "ad_id": "<ad_id>"
    },
    "name": "get_ad"
  }
}

Input Schema

NameRequiredDescriptionDefault
ad_idYesAd id

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

C2.9/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, openWorldHint=true and destructiveHint=false, so the safety profile is covered structurally. The description adds value by disclosing what content comes back (creative, review_status, serving issues), but says nothing about error behavior for invalid ad_ids or whether the call can be slow.

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?

Nine words with no filler, and the returned-field list is packed up front. It loses a point for being a noun-phrase fragment that omits the action verb rather than a complete, self-standing sentence.

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?

For a single-parameter read tool whose annotations already carry the safety profile and with no output schema to explain, the description is close to sufficient. It is still thin on disambiguation from sibling getters and on failure modes, leaving small but real 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 100% with a single required ad_id parameter that carries a pattern and description, so the schema does the heavy lifting. The description adds no format, syntax, or scoping detail beyond what the schema provides, making the baseline 3 correct.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description identifies the resource (a single ad) and names three fields it returns (creative, review_status, serving issues), which makes the shape of the result inferable. However, it is a sentence fragment with no verb, so it never explicitly says it fetches/retrieves, and it does no work to distinguish itself from siblings like get_ad_group or measurement_get_ads_breakdown.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no guidance on when to use this versus list_ads, measurement_get_ads_breakdown, or the other get_* tools, and no stated prerequisites such as required fields or permissions. The agent must infer usage purely from the name.

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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