Gumroad MCP Server

The Gumroad MCP Server bridges the gap between AI assistants and the Gumroad commerce platform by exposing the full breadth of Gumroad’s RESTful API through the Model Context Protocol. This enables Claude Desktop and other MCP‑compatible clients to query, manipulate, and visualize sales data, product catalogs, and promotional codes without leaving the conversational interface. The server authenticates via a user‑generated access token, ensuring that every request is scoped to the developer’s own Gumroad account and respects platform security best practices.

For developers building data‑driven workflows, the server offers a concise set of tools that mirror Gumroad’s core resources: Products, Sales, Offer Codes, and User. Each tool is a single, well‑documented function that performs a specific API call—such as listing all products, disabling a product, or creating a new offer code with a custom discount. Because these tools are available as part of the MCP schema, they can be invoked directly from prompts or integrated into more complex scripts that chain multiple operations together. This tight coupling eliminates the need for separate SDKs or manual HTTP requests, allowing rapid prototyping and iteration.

Key capabilities include:

• Real‑time analytics: Ask the assistant to compare monthly sales, generate charts, or list top‑selling products. The server fetches fresh data from Gumroad’s endpoints and returns it in a format ready for visualization.
• Product lifecycle management: Enable or disable products, retrieve detailed product metadata, and update inventory status—all through conversational commands.
• Dynamic offer code handling: Create, update, or delete promotional codes on the fly, which is invaluable for time‑sensitive campaigns and A/B testing.
• User insight: Retrieve authenticated user details to personalize dashboards or audit access.

Typical use cases span e‑commerce analytics, marketing automation, and rapid product launch management. A designer could ask for a month‑over‑month trend of their flagship book, receive an interactive chart, and then immediately disable a low‑performing product—all without leaving the chat. A marketer might generate a bulk list of offer codes for a holiday sale and upload them to an email campaign, while a data analyst could pull historical sales into a spreadsheet for deeper modeling.

Integration with AI workflows is straightforward: the MCP server registers its tools in the client’s tool registry, and each tool exposes a natural language description that Claude can surface as suggestions. Developers can embed these calls in larger prompts, create custom chains with other MCP services (e.g., database or analytics tools), and even trigger them from scheduled workflows. The result is a seamless, conversational bridge between Gumroad’s commerce engine and the creative potential of AI assistants.