Shopify MCP Proxy & Mock Server

The ShopifyMCPMockShop server is a purpose‑built Model Context Protocol (MCP) bridge that lets AI assistants interact with Shopify’s Storefront API in a controlled, transparent, and safe manner. Unlike generic MCP servers that simply forward requests, this implementation is tightly coupled to Shopify’s evolving API ecosystem and offers a built‑in sandbox via . This allows developers to prototype, test, and debug Shopify workflows without touching a live store, dramatically reducing the risk of accidental data changes or billing surprises.

At its core, the server listens on standard input and output, making it a natural fit for local AI clients such as Claude Desktop or Cursor. It parses MCP messages, translates them into Shopify API calls, and streams back structured responses that include rich ToolAnnotations (e.g., , ). These annotations give the AI a clear understanding of the potential impact of each action, enabling safer decision‑making and better auditability. The server also exposes a comprehensive hierarchy of tools organized by Shopify resource type—products, collections, customers, orders, and more—so developers can quickly discover the exact capabilities available for a given context.

The architecture is deliberately layered: an MCP protocol handler, a Shopify API integration layer, and a sandbox controller that switches between and real store credentials based on environment variables. This separation ensures that the protocol logic remains agnostic to the underlying data source, while the sandbox layer guarantees that destructive operations are only possible when explicitly authorized. The result is a highly reliable, open‑source solution that fills the gap left by many commercial offerings which either lack transparency or impose restrictive usage limits.

Real‑world use cases abound: a frontend developer can ask an AI to generate a new product listing and have it instantly reflected in the mock store, then review the generated GraphQL mutation before committing it to production; a QA engineer can orchestrate end‑to‑end order flows, verify payment processing logic, and capture detailed logs; a product manager can simulate inventory changes to forecast demand without affecting live data. In each scenario, the MCP server acts as a trusted execution engine that bridges natural language intent to concrete API interactions while preserving safety and auditability.

By integrating seamlessly into existing AI workflows, the ShopifyMCPMockShop server empowers developers to iterate faster, reduce bugs, and maintain full control over their Shopify integrations—all within a single, well‑documented MCP service.