Claude-skill-registry acp-checkout-mcp

Implement ACP checkout as an MCP server, exposing checkout operations as MCP tools. Use when building an MCP-based commerce server for AI agents that use tool-calling to complete purchases.

install

source · Clone the upstream repo

git clone https://github.com/majiayu000/claude-skill-registry

Claude Code · Install into ~/.claude/skills/

T=$(mktemp -d) && git clone --depth=1 https://github.com/majiayu000/claude-skill-registry "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/other/other/acp-checkout-mcp" ~/.claude/skills/majiayu000-claude-skill-registry-acp-checkout-mcp && rm -rf "$T"

manifest: skills/other/other/acp-checkout-mcp/SKILL.md

ACP Checkout — MCP Binding

Before writing code

Fetch live docs:

Web-search

acp agentic commerce protocol MCP server implementation

for MCP binding guidance

Fetch

https://developers.openai.com/commerce/specs/checkout/

for checkout operation semantics

Web-search

site:github.com agentic-commerce-protocol MCP

for any official MCP examples

Fetch MCP SDK docs: web-search

site:github.com modelcontextprotocol python-sdk

typescript-sdk

for current SDK

Conceptual Architecture

What MCP Binding Means

ACP's REST checkout operations can be exposed as MCP tools via an MCP server. This allows AI agents that use tool-calling (Claude, ChatGPT, Gemini) to invoke checkout operations directly as tools rather than making raw HTTP calls.

Mapping REST to MCP Tools

Each REST checkout operation becomes an MCP tool:

REST Operation	MCP Tool Name	Description
POST /checkout_sessions	`create_checkout_session`	Create a new checkout session with items
POST /checkout_sessions/{id}	`update_checkout_session`	Update session (items, address, fulfillment)
GET /checkout_sessions/{id}	`get_checkout_session`	Retrieve current session state
POST /checkout_sessions/{id}/complete	`complete_checkout_session`	Submit payment to finalize
POST /checkout_sessions/{id}/cancel	`cancel_checkout_session`	Cancel the session

Tool Input Schemas

Each MCP tool accepts JSON input matching the corresponding REST request body. The tool's

inputSchema

should be derived from the ACP OpenAPI spec's request schemas.

Tool Output

Each tool returns the CheckoutSession object (or error) as JSON, matching the REST response body.

MCP Server Architecture

AI Agent (Claude/ChatGPT)
    ↓ tool call (JSON-RPC)
MCP Server (your code)
    ↓ business logic
Checkout Service (same logic as REST)
    ↓ payment
PSP (Stripe)

The MCP server wraps the same business logic that the REST endpoints use. The checkout service layer should be shared between REST and MCP bindings.

Key Considerations

Idempotency — MCP doesn't have HTTP headers, so pass
```
idempotency_key
```
as a tool parameter
API versioning — Include
```
api_version
```
as a tool parameter or server configuration
Authentication — MCP transport handles auth (stdio for local, SSE/streamable-HTTP for remote)
Error handling — Return ACP error objects as tool errors with the same
```
type
```
/
```
code
```
/
```
message
```
structure
Statelessness — Each tool call should be stateless; session state lives in the CheckoutSession object

Use Cases

AI agents that prefer tool-calling over raw HTTP
Claude Desktop / Claude Code integrations
Multi-agent architectures where commerce is one capability
Rapid prototyping without building a full REST server

Best Practices

Share the checkout business logic layer between REST and MCP bindings
Derive tool input schemas from the ACP OpenAPI spec (don't hand-write them)
Include descriptive tool descriptions so the agent understands when to use each tool
Test with the MCP Inspector before connecting to an agent

Fetch the latest ACP OpenAPI spec and MCP SDK documentation for exact schemas and server setup before implementing.