ucp-checkout-mcp

Implement UCP Checkout over the MCP (Model Context Protocol) binding — expose checkout operations as MCP tools for AI agents. Use when building an MCP server that AI agents like Claude or Gemini can call for commerce, or when integrating with Shopify's MCP endpoint.

17 stars

Best use case

ucp-checkout-mcp is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Implement UCP Checkout over the MCP (Model Context Protocol) binding — expose checkout operations as MCP tools for AI agents. Use when building an MCP server that AI agents like Claude or Gemini can call for commerce, or when integrating with Shopify's MCP endpoint.

Teams using ucp-checkout-mcp should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/ucp-checkout-mcp/SKILL.md --create-dirs "https://raw.githubusercontent.com/OrcaQubits/agentic-commerce-skills-plugins/main/dist/antigravity/ucp-agentic-commerce/.agent/skills/ucp-checkout-mcp/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/ucp-checkout-mcp/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How ucp-checkout-mcp Compares

Feature / Agentucp-checkout-mcpStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Implement UCP Checkout over the MCP (Model Context Protocol) binding — expose checkout operations as MCP tools for AI agents. Use when building an MCP server that AI agents like Claude or Gemini can call for commerce, or when integrating with Shopify's MCP endpoint.

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

# UCP Checkout — MCP Binding

## Before writing code

**Fetch live spec**: Web-search `site:ucp.dev specification checkout-mcp` and fetch the page for exact tool definitions, JSON-RPC envelope format, and `_meta` requirements.

For Shopify's production MCP server, fetch https://shopify.dev/docs/agents/checkout/mcp for auth flow and endpoint details.

## Conceptual Architecture

### How MCP Maps to UCP

UCP over MCP is a **1:1 mapping** of checkout operations to MCP tools using JSON-RPC 2.0. The same data model as REST, different envelope.

### Five MCP Tools

| MCP Tool Name | Maps To | Key Inputs |
|---------------|---------|------------|
| `create_checkout` | POST /checkout-sessions | checkout object + idempotency_key |
| `get_checkout` | GET /checkout-sessions/{id} | id |
| `update_checkout` | PUT /checkout-sessions/{id} | id + checkout object |
| `complete_checkout` | POST .../complete | id + payment_data + idempotency_key |
| `cancel_checkout` | POST .../cancel | id + idempotency_key |

### Meta Requirements

Every MCP tool call MUST include `_meta.ucp.profile` pointing to the platform's UCP profile URI. This replaces the `UCP-Agent` HTTP header from the REST binding.

### Error Mapping

UCP errors embed inside JSON-RPC 2.0 error responses:
- JSON-RPC `error.code`: `-32603` (Internal Error)
- JSON-RPC `error.data`: Contains an `errors[]` array, where each error has `code`, `message`, `severity`, and `details` fields

### When to Use MCP Binding

- You're building a **merchant MCP server** that AI agents (Claude, Gemini, etc.) call via tool use
- You're integrating with an existing MCP server (e.g., Shopify's)
- You want AI agents to autonomously browse and purchase without REST client code

### Implementation Guidance

**Building a Business MCP Server:**
1. Implement the 5 tools using your MCP framework (e.g., `@modelcontextprotocol/sdk` for Node, `mcp` for Python)
2. Extract `_meta.ucp.profile` from every tool call for negotiation
3. Return checkout objects as JSON in the MCP tool result
4. Return errors using JSON-RPC error format with UCP data payload
5. Implement idempotency on create and complete tools

**Connecting to an existing MCP server (e.g., Shopify):**
1. Authenticate (Shopify uses OAuth2 client_credentials for access tokens)
2. Connect to the MCP endpoint
3. Call tools with proper `_meta.ucp.profile` and checkout payloads
4. Parse tool results for checkout status and messages

### Shopify MCP Integration

Shopify provides a production MCP server for UCP checkout. Before implementing:
- Fetch https://shopify.dev/docs/agents/checkout/mcp for the latest auth flow, endpoint URL format, and error codes
- Authentication uses `POST https://api.shopify.com/auth/access_token` with client credentials
- MCP endpoint is `POST https://{shop-domain}/api/ucp/mcp`

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