# Gumroad — how to use (mcp.ai)

Gumroad simplifies selling digital goods, physical products, and memberships by offering a streamlined checkout, marketing tools, and direct payout options

## Option A — via MCP (recommended)
Remote MCP endpoint (HTTP, streamable): `https://api.mcp.ai/p_gumroad?ms=1781542980000`
Add it as a custom/remote MCP connector in your client (Claude, Cursor, VS Code…), then authenticate when prompted. Once connected, ask the agent to use the server's tools (e.g. `gumroad_get_resource_subscriptions`).

## Option B — via direct REST API
Base URL: `https://api.mcp.ai/api/gumroad`
Auth: `Authorization: Bearer sk_live_…` — create a workspace API key at https://mcp.ai/settings/api-keys
Discover endpoints: `GET https://api.mcp.ai/api/gumroad/_endpoints`

### Endpoints
- `POST https://api.mcp.ai/api/gumroad/get/resource/subscriptions` — Tool to show all active subscriptions of the user for the input resource. use when you need to review existing webhooks before adding a new one.
  - body: { resource_name: string }
- `POST https://api.mcp.ai/api/gumroad/get/sales` — Tool to retrieve all successful sales by the authenticated user. use when you need to list your gumroad sales, optionally filtering by email, date range, product, or pagination.
  - body: { page?: integer, after?: string, email?: string, before?: string, product_id?: string }
- `POST https://api.mcp.ai/api/gumroad/get/user` — Tool to retrieve the authenticated user's data. use when you need the current user's profile details after authentication.
- `POST https://api.mcp.ai/api/gumroad/subscribe/to/resource` — Tool to subscribe to a resource. use when you need to receive real-time event webhooks after creating your webhook endpoint.
  - body: { post_url: string, resource_name: string }
- `POST https://api.mcp.ai/api/gumroad/unsubscribe/from/resource` — Tool to unsubscribe from a resource. use after verifying the subscription id exists to remove webhook.
  - body: { resource_subscription_id: string }

## More
- Page: https://mcp.ai/gumroad
- Agent spec (llms.txt): https://mcp.ai/gumroad/llms.txt
- Postman collection: https://mcp.ai/gumroad/postman.json