Style Arcade MCP connects AI assistants to your live fashion retail data, analytics and merchandising intelligence using Model Context Protocol (MCP). It gives buying and merchandising teams the context to ask questions about products, performance and future assortment plans, without rebuilding that context in every prompt.

Connecting an LLM directly to a retail data warehouse gives it access to your data, not an understanding of merchandising. It still needs to know how your metrics work, how products relate, what happened over time and the merchandising logic behind the numbers.
Style Arcade provides that analytics and merchandising layer, so your team doesn’t have to recreate the context in every prompt.

A chatbot gives you a conversational interface. It doesn’t give the AI the merchandising intelligence to answer well.
A chatbot connected directly to your data can retrieve information, but it still needs the merchandising context to interpret it correctly. Style Arcade brings your products, metrics, history, planning data and merchandising logic together before the AI answers. So your team gets more than a chat window on top of raw data.

The same number can mean very different things in retail. Merchandising context helps AI understand what a metric means, not just what the number says.
A style with strong sell-through might look like something to buy again, until you realise those units moved at heavy markdown. Style Arcade gives AI the merchandising context behind the metric, not just the metric itself.

Access to future POs isn’t the same as understanding a future assortment. Your data warehouse can show AI what sold and what’s on order, but it doesn’t give it the merchandising context to understand the range those products are building.
Style Arcade understands your future assortment as a range, helping AI account for what’s already planned and spot duplication, gaps and opportunities before you buy.

Style Arcade gives AI the merchandising context and defined metrics it needs to interpret your business data, rather than leaving it to infer how your numbers work.
Answers can also be traced back to the underlying analysis, so your team can verify the workings rather than taking an AI-generated answer at face value.

Style Arcade MCP removes much of the manual preparation buying and merchandising teams need to do before they can start analysing trade. Instead of exporting data, stitching together reports and preparing analysis before a trade meeting, your team can start with the question and investigate from there.
It’s not just about getting answers faster. It’s about getting to the work that matters faster.

MCP means your retail intelligence doesn’t have to be tied to whichever AI model happens to be best today.
It separates your Style Arcade data and merchandising intelligence from the AI you choose to use, giving you the flexibility to use the agent and model that works best for your business and switch as the technology evolves.

Yes. Style Arcade MCP is designed to give you model choice rather than locking your business into one LLM.
As models improve, your team can move with them without rebuilding the merchandising intelligence and business context underneath.
Best in class, without being locked in.

No manual exports or re-uploads are required. MCP connects to your live Style Arcade environment, so the AI can work with the business context already held within Style Arcade.

Style Arcade MCP is built on Amazon Bedrock and connects securely to your Style Arcade environment. Your existing data permissions are respected, data is encrypted in transit and at rest, and your business data isn’t used to train underlying AI models. Your data stays yours.