This report shows how Colter reviews storefront content, catalog signals, evidence quality, and next actions.
Agents can find Moon Trail Outfitters products and read prices, images, and availability on sampled pages. The biggest gaps are catalog identifiers and policy markup - both covered in the fix plan.
Browser agents can identify the safe cart actions instead of guessing from visual buttons.
Review this code before applying it to your store.
Get your fix plan{
"webmcp": "draft-2026",
"store": "moontrailoutfitters.com",
"tools": [
{
"name": "cart.add",
"description": "Add a Moon Trail product variant to cart",
"method": "POST",
"action": "/cart/add",
"params": {
"id": { "source": "variant_id", "required": true },
"quantity": { "type": "integer", "minimum": 1, "default": 1 }
}
},
{
"name": "cart.update",
"description": "Update quantity for a cart line",
"method": "POST",
"action": "/cart/change",
"params": {
"line": { "type": "integer", "minimum": 1 },
"quantity": { "type": "integer", "minimum": 0 }
}
}
]
}Every finding is labeled by how much evidence backs it.
Colter found a usable Shopify catalog foundation, but identifiers and policy fields are incomplete and the agent catalog surface is not verified.
Runtime validation is still required before saying agents can complete purchase journeys.
Structured product evidence exists, but no public UCP catalog or checkout manifest was found.
KEY GAPS
ChatGPT can read product pages, but no ACP purchase endpoint was detected.
KEY GAPS
No MCP tools or llms.txt guidance were found for Claude-style tool use.
KEY GAPS
Product search forms are annotated, but checkout tools are not exposed.
KEY GAPS
One script tag. Real-time traffic.
500 free agent visits. No credit card required.
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