How to Use the VTEX Checkout MCP in AutoGen

Q: Can I use AutoGen to compare different simulated payment methods in VTEX Checkout?

Yes. You can set up multiple agents, each calling simulatepayment with different inputs (e.g., Visa vs. PayPal). They debate the results and present a consensus on which method is best for the user.

Let multiple agents debate the best checkout path with AutoGen's VTEX Checkout decision system.

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Connect VTEX Checkout MCP to AutoGen

Create your Vinkius account to connect VTEX Checkout to AutoGen and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup VTEX Checkout with AutoGen

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Consensus-Driven Pricing

You can set up two agents: a 'Pricing Agent' and an 'Order Agent.' The Pricing Agent calls `simulate_order` to get the base cost. The Order Agent then challenges that result by calling `add_coupon`, forcing the system to reach consensus on the final, correct price. This debate mechanism is key. Instead of just running a tool, AutoGen makes agents discuss which tools are needed and in what sequence to settle on one definitive answer.

Multi-Step Profile Validation

Designate a 'Security Agent' to first call `get_client_profile` for validation. Then, have an 'Address Agent' use the data from the profile to decide if `create_address` is necessary or if the client already has valid details. The agents argue through the process, ensuring that the final action—like simulating a payment—is only attempted after all required checks are passed.

Payment Strategy Negotiation

Build an 'Efficiency Agent' to run `get_orderform` and pass the data. A separate 'Validation Agent' then uses this input to call `simulate_payment`. If the payment fails, they debate which parameters need changing before retrying. This is ideal for complex scenarios where success isn't obvious and requires competing perspectives to converge on a single actionable decision.

Setup guide

Set up VTEX Checkout MCP in AutoGen

Prerequisites

Python 3.10+ installed
autogen-ext[mcp] package
Active Vinkius subscription with a valid endpoint token

1

Install AutoGen with MCP
Run pip install "autogen-ext[mcp]" autogen-agentchat. The MCP extension includes mcp_server_tools for stateless tool access.
2

Fetch tools from the MCP
Call mcp_server_tools(SseServerParams(url=...)) with your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Run your agent
Pass the tools to AssistantAgent and call agent.run(). The agent invokes VTEX Checkout tools and returns structured results.

agent.py

from autogen_ext.tools.mcp import SseServerParams, mcp_server_tools
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

server_params = SseServerParams(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

tools = await mcp_server_tools(server_params)

agent = AssistantAgent(
    name="VTEX Checkout_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent VTEX Checkout data")
print(result.messages[-1].content)

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Prerequisites

Python 3.10+ installed
autogen-ext[mcp] + autogen-agentchat
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Same packages as above. McpWorkbench is ideal when your agent needs stateful sessions across multiple tool calls.
2

Use McpWorkbench as context manager
Wrap your agent in async with McpWorkbench(...) to maintain shared state and resources. The workbench manages the full MCP session lifecycle.
3

Run with workbench
Pass workbench=workbench to your agent. State is preserved across multiple tool calls within the same session.

agent.py

from autogen_ext.tools.mcp import McpWorkbench, SseServerParams
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

server_params = SseServerParams(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

async with McpWorkbench(server_params) as workbench:
    agent = AssistantAgent(
        name="VTEX Checkout_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent VTEX Checkout data")
    print(result.messages[-1].content)

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Common questions about VTEX Checkout MCP in AutoGen

AutoGen doesn't just execute tools; it makes agents debate them. For instance, one agent might check `get_orderform` while another determines if a coupon is needed via `add_coupon`, and they negotiate the final cart state.

Yes. You can set up multiple agents, each calling `simulate_payment` with different inputs (e.g., Visa vs. PayPal). They debate the results and present a consensus on which method is best for the user.

It's perfect. You can have agents debate whether new contact information is needed, leading to the controlled execution of `create_address` only when consensus deems it necessary.

The system handles this by having different agents sequentially call tools like `simulate_order` and then using the output to inform a subsequent agent's decision, creating a robust simulation.

This server touches cart item details and coupon codes when running `add_coupon` or `get_orderform`. The agent framework ensures these inputs are handled securely during deliberation.

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