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How to Use the Kavak MCP in AutoGen

Deploy AutoGen agents to debate vehicle selections and manage Kavak reservations using this MCP Server.

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AutoGen

Connect Kavak MCP to AutoGen

Create your Vinkius account to connect Kavak 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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Debate vehicle condition with AutoGen agents

`get_vehicle_inspection` brings the 240-point mechanical breakdown into your multi-agent conversation. You can set up one AutoGen agent as a cynical mechanic and another as a value-focused buyer. They will argue over the inspection checklist before agreeing to recommend the car. This prevents your system from pitching lemons to actual buyers.

Coordinate financing plans via this MCP Server

`get_financing_options` spits out monthly payment plans based on the car's price. This MCP Server allows your agents to negotiate different down payments and interest rates in a multi-turn chat. The finance agent matches these terms against the buyer's budget limits. They won't hand off the deal until the math works for both sides.

Manage the reservation flow autonomously

`create_reservation` locks the car and pulls it off the active marketplace. Your AutoGen coordinator agent triggers this hold only after the sales and finance agents sign off on the deal. If the research agent flags an accident history using `get_vehicle_history`, the group halts the purchase. This dynamic workflow stops bad deals before any money changes hands.

Setup guide

Set up Kavak MCP in AutoGen

Prerequisites

  • Python 3.10+ installed
  • autogen-ext[mcp] package
  • Active Vinkius subscription with a valid endpoint token
  1. 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. 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. 3

    Run your agent

    Pass the tools to AssistantAgent and call agent.run(). The agent invokes Kavak 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="Kavak_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

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

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Common questions about Kavak MCP in AutoGen

Use the mcp_server_tools helper with the server's HTTP URL. Pass the generated tool list directly to your AssistantAgent constructor to give them access.
Yes, one agent can call estimate_trade_in while another evaluates market trends with get_market_pricing. They will debate the valuation until they settle on a realistic trade-in target.
The group uses list_locations to find the nearest showroom. Once a location is selected, an agent executes schedule_test_drive to book the appointment.
The agent checks the status using get_reservation to identify the block. It then alerts the other agents to resolve the missing buyer details.
Buyer phone numbers and emails are transmitted directly to Kavak's API via encrypted SSL connections. Vinkius runs the server in an isolated sandbox, keeping transaction details private.

Start using the Kavak MCP today

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