Build agent-readable product feeds using schema.org/Product markup and MCP catalog endpoints so AI agents can discover, compare, and purchase products without scraping

Verified steps

1. Implement JSON-LD structured data using schema.org/Product on every product detail page; minimum required properties for agent readability are: name, description, brand, gtin (or mpn), offers (with price, priceCurrency, availability, url), aggregateRating, and shippingDetails — include MerchantReturnPolicy for policy completeness
2. Publish a product feed in a format compatible with the major agent channels: Google Merchant Center XML/CSV (required for Google Shopping and Universal Cart indexing), and an OpenAI Commerce feed if participating in ACP — Shopify merchants can configure automatic feed sync to multiple channels from the Admin
3. Expose an MCP server endpoint (for example, /api/mcp on your storefront, following the pattern used by Your Next Store and Shopify's official MCP servers) that serves your catalog as MCP-compatible tool responses: search_products, get_product_details, check_inventory, and get_shipping_policy tools at minimum
4. Ensure each SKU entry in the feed and MCP response includes the 12 core agent-readable attributes: title, description, brand, GTIN, MPN, Google Product Taxonomy category, price, sale price, availability, condition, image URL, and product URL — agents cannot reliably disambiguate SKUs without all 12
5. Set a freshness SLA for your feed and MCP responses and publish it; agents and agent orchestrators that cache your data will use the published SLA to determine when to re-query — an unpublished or violated SLA causes agents to surface stale prices or out-of-stock items to buyers
6. Validate your structured data with Google's Rich Results Test and the schema.org validator before submitting to agent channels; agents that parse malformed JSON-LD may silently drop required fields rather than returning an error