MCP is a foundation for agentic AI. Instead of building AI features one integration at a time (ChatGPT plugin for Slack, separate plugin for GitHub), MCP lets any AI model plug into the same tool ecosystem. A merchant builds one MCP server that exposes their product catalog, inventory, and order status—then Claude, GPT-4 with plugins, and other models can all talk to it the same way.
In agentic commerce, MCP powers the bridge between product data and AI agents. An MCP server wraps your product feed, inventory system, and checkout flow with a consistent interface. When an agent needs to check if a ring is in stock or place an order, it calls standardized MCP tools. This decouples your backend from any single AI platform.
Arbling uses MCP to expose the Open Jewelry Schema—a standardized format for jewelry product data. Merchants who adopt the schema can run an MCP server that any agentic system can query. This is critical for multi-agent scenarios: a customer might shop via Claude, their spouse uses Perplexity, and a procurement bot runs on Google's platform—all of them access the same trustworthy data through the same MCP server.
MCP is to AI agents what REST APIs are to web services—a common contract so different clients can integrate without custom work.