Search structured product data and build shopping experiences with Channel3’s API, developer tools and affiliate infrastructure.
Channel3 provides product-discovery infrastructure for applications and AI shopping agents. It brings product information into a consistent structure so a developer can search and recommend items without building a separate connection to every retailer. The service supports several developer interfaces, including an API, SDK, MCP tools and a command-line workflow.
Search requests can begin with text, an image or a product URL. Filters narrow results by attributes such as price, brand, category or dimensions. Responses include structured product details, images, descriptions and offers across retailers. This makes it possible to build a shopping interface around comparable records rather than ask a language model to invent a product list.
Related operations include looking up a URL, finding similar products and browsing collections. Current price and availability information is part of the product data, but the application should still handle changes and confirm the final merchant offer when the user proceeds toward a purchase.
Channel3’s brand partnerships can provide commissions on qualifying sales. That is distinct from a guarantee that every item or transaction earns the same amount. Developers should inspect applicable rates and tracking requirements before presenting affiliate results. The public homepage describes enterprise checkout as forthcoming, so general purchase execution should not be assumed from product-search access alone.
The documentation also supports a conversational shopping agent and price tracking. An agent can use the available interfaces in its own application context, while ordinary account-based API access uses credentials. Machine Payments Protocol offers a separate pay-per-call route without the same signup flow.
Accounts receive a monthly free-credit allowance, with additional credits billed as used. Most requests cost one credit, but some image-detection, conversation and price-tracking operations have different accounting. A developer should estimate the number of calls made by a complete user interaction, not only the initial search. A good first integration checks returned data, handles empty results and preserves the user’s filters before adding recommendation logic or commercial tracking.
