Commerce Cloud MCP Server

The Commerce Cloud MCP Server is a bridge that lets AI assistants—such as Claude or other Model Context Protocol (MCP) clients—talk directly to Salesforce Commerce Cloud. By exposing a set of well‑defined resources, tools, and prompts over MCP, the server translates high‑level AI requests into concrete Open Commerce API (OCAPI) calls. This eliminates the need for custom integration code in every client, allowing developers to focus on building conversational experiences rather than wrestling with REST endpoints and authentication.

At its core, the server provides CRUD operations for products, custom objects, content assets, and orders. It also offers analytical tools that let an assistant surface order patterns or customer insights in natural language. For example, a user can ask the AI to “show me products that sold most in Q2” and receive a ready‑made table of results. In addition, the server can generate or update product descriptions and content bodies from images, turning creative assets into fully populated Commerce Cloud records with minimal human effort.

Key capabilities include:

• Product Management – Create, read, update, and delete product data; automatically generate descriptions from imagery.
• Order Analysis – Pull order histories, aggregate sales metrics, and surface behavioral insights for marketing or inventory decisions.
• Custom Object Operations – Full support for reading, writing, and creating custom objects that extend the Commerce Cloud data model.
• Content Asset Handling – Retrieve existing assets and auto‑generate or update content bodies from design files.
• Environment‑Aware Configuration – Seamlessly switch between development, staging, and production instances via environment variables.

Real‑world use cases abound: a merchandising team can let an AI assistant pull the latest product catalog and suggest new listings, while marketing departments can generate dynamic content for campaigns directly from design mockups. Inventory managers might query order trends to predict stock needs, and developers can prototype new conversational flows that interact with Commerce Cloud without writing API wrappers.

Integration is straightforward for MCP‑aware workflows. Once the server is running, an AI client simply declares a mcpServers entry in its configuration. From there, the assistant can invoke any exposed resource or tool as if it were a local function, with the server handling authentication, rate limiting, and data transformation. This tight coupling means AI assistants can deliver real‑time Commerce Cloud insights in a conversational, context‑aware manner—an advantage that sets the Commerce Cloud MCP Server apart from generic REST integrations.