How do I get my VTEX API credentials?

Log in to your VTEX Admin, go to **Account Settings → Application Keys**, and create a new App Key. You'll receive an App Key and App Token pair. You also need your Account Name (the subdomain you use to access the VTEX Admin, e.g., 'mystore'). No code, no SDK — just connect and go.

Can my agent simulate a full cart with shipping costs?

Yes! Use the 'simulate_order' tool with a list of items and a postal code. Your agent will return the full cart breakdown — totals, per-item pricing, available logistics options, estimated delivery dates, and applicable discounts — all without touching the actual store.

What happens when a customer asks support about their current cart?

Your support agent can use the 'get_orderform' tool to instantly retrieve the customer's active cart — items, quantities, prices, applied coupons, and shipping address. No need to switch tabs or navigate the admin. The agent can then apply a coupon or check shipping costs, all within the same conversation.

Can I validate payment conditions before placing bulk orders?

Absolutely. The 'simulate_payment' tool lets your agent validate payment tokens and check accepted conditions — perfect for operations teams running bulk order validations across multiple sellers and payment methods without processing real transactions.

VTEX Checkout MCP Server for LangChain 6 tools — connect in under 2 minutes

Name: VTEX Checkout
Availability: InStock
Author: Vinkius

python.langchain.com/docs/integrations/tools/mcp

Built by Vinkius GDPR 6 Tools Framework

LangChain is the leading Python framework for composable LLM applications. Connect VTEX Checkout through the Vinkius and LangChain agents can call every tool natively — combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

import asyncio
from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain_openai import ChatOpenAI
from langgraph.prebuilt import create_react_agent

async def main():
    # Your Vinkius token — get it at cloud.vinkius.com
    async with MultiServerMCPClient({
        "vtex-checkout": {
            "transport": "streamable_http",
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
        }
    }) as client:
        tools = client.get_tools()
        agent = create_react_agent(
            ChatOpenAI(model="gpt-4o"),
            tools,
        )
        response = await agent.ainvoke({
            "messages": [{
                "role": "user",
                "content": "Using VTEX Checkout, show me what tools are available.",
            }]
        })
        print(response["messages"][-1].content)

asyncio.run(main())

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* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About VTEX Checkout MCP Server

Connect your VTEX e-commerce checkout API to any AI agent and streamline your store's pre-purchase operations through natural conversation.

LangChain's ecosystem of 500+ components combines seamlessly with VTEX Checkout through native MCP adapters. Connect 6 tools via the Vinkius and use ReAct agents, Plan-and-Execute strategies, or custom agent architectures — with LangSmith tracing giving full visibility into every tool call, latency, and token cost.

What you can do

Cart Simulation — Run complete order simulations with items, quantities, and sellers to instantly preview totals, discounts, and available shipping options for any postal code.
Shopping Cart Management — Retrieve the full state of any active shopping cart (orderform), including items, client profile, payment conditions, and logistics.
Coupon Management — Apply discount coupons to active carts and immediately see the impact on totals.
Client Profiles — Look up registered client profiles by user ID — retrieve name, CPF/CNPJ, email, and contact details.
Address Management — Register new shipping addresses for clients, streamlining the checkout flow.
Payment Simulation — Validate payment tokens and simulate payment conditions before placing an order.

The VTEX Checkout MCP Server exposes 6 tools through the Vinkius. Connect it to LangChain in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect VTEX Checkout to LangChain via MCP

Follow these steps to integrate the VTEX Checkout MCP Server with LangChain.

Install dependencies

Run pip install langchain langchain-mcp-adapters langgraph langchain-openai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save the code and run python agent.py

Explore tools

The agent discovers 6 tools from VTEX Checkout via MCP

Why Use LangChain with the VTEX Checkout MCP Server

LangChain provides unique advantages when paired with VTEX Checkout through the Model Context Protocol.

The largest ecosystem of integrations, chains, and agents — combine VTEX Checkout MCP tools with 500+ LangChain components

Agent architecture supports ReAct, Plan-and-Execute, and custom strategies with full MCP tool access at every step

LangSmith tracing gives you complete visibility into tool calls, latencies, and token usage for production debugging

Memory and conversation persistence let agents maintain context across VTEX Checkout queries for multi-turn workflows

VTEX Checkout + LangChain Use Cases

Practical scenarios where LangChain combined with the VTEX Checkout MCP Server delivers measurable value.

RAG with live data: combine VTEX Checkout tool results with vector store retrievals for answers grounded in both real-time and historical data

Autonomous research agents: LangChain agents query VTEX Checkout, synthesize findings, and generate comprehensive research reports

Multi-tool orchestration: chain VTEX Checkout tools with web scrapers, databases, and calculators in a single agent run

Production monitoring: use LangSmith to trace every VTEX Checkout tool call, measure latency, and optimize your agent's performance

VTEX Checkout MCP Tools for LangChain (6)

These 6 tools become available when you connect VTEX Checkout to LangChain via MCP:

add_coupon

Apply a coupon to a shopping cart

create_address

Add a new address to a client profile

get_client_profile

Get client profile details

get_orderform

Get details of a specific shopping cart

simulate_order

Simulate a cart and shipping costs

simulate_payment

Simulate a payment validation

Example Prompts for VTEX Checkout in LangChain

Ready-to-use prompts you can give your LangChain agent to start working with VTEX Checkout immediately.

"Simulate a cart with 2 units of product ID 1234 and shipping to ZIP 01310-100"

"Apply coupon code SUMMER20 to orderform abc123"

"Look up the client profile for user ID 98765"

Troubleshooting VTEX Checkout MCP Server with LangChain

Common issues when connecting VTEX Checkout to LangChain through the Vinkius, and how to resolve them.

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

VTEX Checkout + LangChain FAQ

Common questions about integrating VTEX Checkout MCP Server with LangChain.

How does LangChain connect to MCP servers?

Use langchain-mcp-adapters to create an MCP client. LangChain discovers all tools and wraps them as native LangChain tools compatible with any agent type.

Which LangChain agent types work with MCP?

All agent types including ReAct, OpenAI Functions, and custom agents work with MCP tools. The tools appear as standard LangChain tools after the adapter wraps them.