How to Use the VTEX Checkout MCP in OpenAI Agents SDK
Build production-grade e-commerce logic with the OpenAI Agents SDK.
Works with every AI agent you already use
…and any MCP-compatible client
Connect VTEX Checkout MCP to OpenAI Agents SDK
Create your Vinkius account to connect VTEX Checkout to OpenAI Agents SDK and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.
Process Checkout Data via MCP Server
Need to know if a customer can afford it? The agent handles complex simulations. You use `simulate_order` to get total cart costs, and then run `simulate_payment` against those figures. This lets your system check both shipping rates and payment eligibility before finalizing anything.
Managing Customer Details
The agent keeps track of who the user is. It can fetch existing details using `get_client_profile`, or if they're new, it runs `create_address` so you don't have to ask for everything twice. This makes the checkout process much smoother.
Applying Promotions and Coupons
Don't let customers forget their discount. You run `add_coupon` with a specific code, which applies the percentage or fixed amount right to the current cart total. This tool handles the calculation so your agent knows exactly what the final price should be.
Set up VTEX Checkout MCP in OpenAI Agents SDK
Prerequisites
- Python 3.10+ installed
-
openai-agentspackage (pip install openai-agents) - Active Vinkius subscription with a valid endpoint token
- 1
Install the SDK
Run
pip install openai-agentsto install the OpenAI Agents SDK. The MCP integration is built-in — no extra dependencies needed. - 2
Connect via SSE transport
Use
MCPServerSsewith your Vinkius endpoint URL. Replace[YOUR_TOKEN_HERE]with your token from cloud.vinkius.com. The SDK auto-discovers all VTEX Checkout tools at runtime. - 3
Create your Agent
Pass the MCP to
Agent(mcp_servers=[server]). The agent receives VTEX Checkout tools as native definitions — JSON schemas resolve automatically. - 4
Run the agent
Call
Runner.run(agent, prompt)to execute. The agent invokes the appropriate VTEX Checkout tools and returns structured results. Copy the full example on the right to get started.
import asyncio
from agents import Agent, Runner
from agents.mcp import MCPServerSse
async def main():
async with MCPServerSse(
url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
) as server:
agent = Agent(
name="VTEX Checkout Agent",
instructions="You have access to VTEX Checkout tools.",
mcp_servers=[server],
)
result = await Runner.run(agent, "List recent transactions")
print(result.final_output)
asyncio.run(main()) Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by VTEX. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.
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Common questions about VTEX Checkout MCP in OpenAI Agents SDK
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