How to Use the Kyte MCP in OpenAI Agents SDK

Q: Can I trace Kyte transaction queries in real time?

Every call to tools like listfinancialtransactions appears instantly in your OpenAI developer dashboard. You see the exact input parameters, the raw JSON payload returned, and the token usage for each turn through this MCP Server connection.

Connect your POS store to the OpenAI Agents SDK to automate order lookups and run secure inventory checks.

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Connect Kyte MCP to OpenAI Agents SDK

Create your Vinkius account to connect Kyte 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 Kyte with OpenAI Agents SDK

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Run secure inventory checks with OpenAI Agents SDK

`get_inventory_status` connects your OpenAI agent directly to your physical stock levels. Because the SDK runs guardrails before executing any tool call, your agent checks inventory without making unauthorized changes to product listings. If stock runs low, the agent triggers `get_product_details` to pull the exact SKU. The built-in tracing on the OpenAI dashboard logs every single inventory query, giving you a clear audit trail of what your agent looked up.

Resolve store orders using this MCP Server

`list_kyte_orders` allows your agent to pull recent transactions and immediately flag delivery delays. By using this MCP Server, the agent handles customer complaints on autopilot by matching order history with real-time shipping logs. When an order needs a refund, the agent executes `get_order_details` to verify the purchase amount. This setup keeps your support agents focused on complex issues while the automated system handles routine status checks.

Coordinate customer lookups across specialized agents

`list_kyte_customers` feeds raw buyer data to your primary routing agent. The OpenAI Agents SDK then hands off the task to a specialized profile agent that runs `get_customer_profile` to extract buying habits. This handoff ensures that personal contact details remain isolated within the specific agent assigned to customer relations. Your main agent never sees sensitive information, reducing your security footprint while processing store data.

Setup guide

Set up Kyte 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 Kyte tools at runtime.
3

Create your Agent

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

Run the agent

Call Runner.run(agent, prompt) to execute. The agent invokes the appropriate Kyte 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="Kyte Agent",
            instructions="You have access to Kyte tools.",
            mcp_servers=[server],
        )
        result = await Runner.run(agent, "List recent transactions")
        print(result.final_output)

asyncio.run(main())

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Common questions about Kyte MCP in OpenAI Agents SDK

Install the SDK using pip, then initialize the streamable HTTP connection pointing to your Vinkius endpoint. Pass the server instance directly into your Agent constructor by registering the MCP Server with your agent list, and the model will auto-discover the tools.

Yes, you can control access through the agent configuration or by defining strict system instructions. This prevents the agent from running write operations when it only needs to check stock levels.

The SDK relies on the underlying HTTP client to handle retries. If the store API returns a rate limit error, the agent pauses execution and retries the request automatically.

Every call to tools like `list_financial_transactions` appears instantly in your OpenAI developer dashboard. You see the exact input parameters, the raw JSON payload returned, and the token usage for each turn through this MCP Server connection.

All transaction details, order histories, and customer profiles remain inside the Vinkius V8 sandbox. The OpenAI Agents SDK only receives the specific data returned by the tools, with no persistent storage on external servers.

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