How to Use the Kavak MCP in OpenAI Agents SDK

Q: Can my OpenAI Agents SDK pipeline hold a Kavak vehicle?

Yes. The createreservation tool requires buyer contact details and actively takes the car off the market. You should use OpenAI's guardrails to require human approval before your agent executes this hold.

Q: How does the agent know which Kavak locations offer home test drives?

It calls listlocations. This returns the address, operating hours, and specific services for each physical hub. The agent cross-references this with the buyer's zip code to book via scheduletestdrive.

Build production-grade agents that trade, finance, and reserve used cars using the OpenAI Agents SDK.

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Connect Kavak MCP to OpenAI Agents SDK

Create your Vinkius account to connect Kavak 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.

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Setup Kavak with OpenAI Agents SDK

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Browse Mexican Inventory with the Kavak MCP Server

Your agent uses `search_vehicles` to pull real-time inventory from Mexico's largest used car platform. It filters by make, model, and year, combining `list_makes` and `list_models` to narrow down exact matches for your buyer. You do not have to worry about the agent hallucinating specs. Because OpenAI Agents SDK auto-discovers these endpoints, the agent pulls exact details via `get_vehicle` and feeds them straight into your production tracing dashboard.

Audit Cars Before Buying

The `get_vehicle_inspection` tool grabs the 240-point mechanical report for any car on the lot. Your specialized underwriting agent reviews this data alongside `get_vehicle_history` to catch past accidents or title issues. You configure the handoff. One agent audits the mechanicals, then passes the clean bill of health to a pricing agent that runs `get_market_pricing`. If the math checks out, the pipeline moves forward.

Lock Down Inventory and Finance

You can pull exact loan structures using `get_financing_options` while simultaneously running `estimate_trade_in` on the buyer's current car. The agent calculates the net cost based on current Mexican market prices and local condition factors. When the buyer is ready, the agent executes `create_reservation` to pull the vehicle off the public marketplace. You can also trigger `schedule_test_drive` to set up a home delivery in select cities, all verified by OpenAI's built-in action guardrails before the API call fires.

Setup guide

Set up Kavak MCP in OpenAI Agents SDK

Prerequisites

Python 3.10+ installed
openai-agents package (pip install openai-agents)
Active Vinkius subscription with a valid endpoint token

1

Install the SDK

Run pip install openai-agents to install the OpenAI Agents SDK. The MCP integration is built-in — no extra dependencies needed.
2

Connect via SSE transport

Use MCPServerSse with your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. The SDK auto-discovers all Kavak tools at runtime.
3

Create your Agent

Pass the MCP to Agent(mcp_servers=[server]). The agent receives Kavak tools as native definitions — JSON schemas resolve automatically.
4

Run the agent

Call Runner.run(agent, prompt) to execute. The agent invokes the appropriate Kavak tools and returns structured results. Copy the full example on the right to get started.

agent.py

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="Kavak Agent",
            instructions="You have access to Kavak tools.",
            mcp_servers=[server],
        )
        result = await Runner.run(agent, "List recent transactions")
        print(result.final_output)

asyncio.run(main())

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Kavak. 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 Kavak MCP in OpenAI Agents SDK

Install openai-agents via pip. Create an MCPServerStreamableHttp instance with your endpoint URL and pass it into the mcp_servers array in your Agent constructor. Set cacheToolsList=True to speed up the initial tool discovery.

Yes. The create_reservation tool requires buyer contact details and actively takes the car off the market. You should use OpenAI's guardrails to require human approval before your agent executes this hold.

It calls list_locations. This returns the address, operating hours, and specific services for each physical hub. The agent cross-references this with the buyer's zip code to book via schedule_test_drive.

The SDK handles basic retries, but you should monitor your tracing dashboard. If you hammer search_vehicles too fast, the connection will throttle.

The server processes raw buyer names, phone numbers, and addresses when you call create_reservation. The V8 Isolate Sandbox destroys the execution environment the moment the reservation confirms, leaving zero residual buyer data in memory.

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