How to Use the ezyVet MCP in OpenAI Agents SDK

Build production-grade veterinary agents using the ezyVet MCP Server and OpenAI Agents SDK.

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Connect ezyVet MCP to OpenAI Agents SDK

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

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Perplexity

Real-time patient record lookups

Your agent pulls live medical history directly from your practice data. It uses `get_animal` to grab specific patient files the second you need them. Stop digging through manual tabs. The OpenAI Agents SDK handles these requests instantly so you can focus on the exam room.

Automated appointment scheduling

Keep your daily calendar synced by querying `list_appointments` through your agent. You get immediate visibility into your daily throughput without opening another window. This keeps your workflow moving. The agent processes the list and alerts you to any gaps or conflicts before they turn into bottlenecks.

Financial tracking in the agent

Check outstanding balances or specific charges by invoking `list_invoices` or `get_invoice`. Your agent retrieves the exact figures from ezyVet for quick review. Accuracy matters when you are dealing with billing. This integration ensures your agent relies on the source of truth, not a guess.

Setup guide

Set up ezyVet 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 ezyVet tools at runtime.
3

Create your Agent

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

Run the agent

Call Runner.run(agent, prompt) to execute. The agent invokes the appropriate ezyVet 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="ezyVet Agent",
            instructions="You have access to ezyVet 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 ezyVet MCP in OpenAI Agents SDK

Use the MCPServerStreamableHttp class to point your agent at the server URL. Pass the instance into your agent constructor to let it auto-discover available tools.

Yes. Since you are hosting this via Vinkius, it uses ephemeral connections and standard token-based auth. Your agent only sees what you explicitly allow.

The server handles the heavy lifting by fetching only what you need. By using `list_animals` or `list_consults` with specific filters, you keep your context window clean.

The data is pulled directly from the source. Your agent reads the raw response, ensuring that the clinical records you see match the system state.

Your patient records never leave your environment unnecessarily. The server acts as a bridge, and Vinkius ensures that sensitive data like client contact info remains isolated.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

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