How to Use the TurfHop MCP in OpenAI Agents SDK

Q: How do I use TurfHop with OpenAI Agents SDK for job scheduling?

The OpenAI Agents SDK allows you to call createjob directly. You simply provide the necessary job data in a JSON string, and your agent handles passing that payload securely through the MCP Server.

Q: What if I need to check existing customer records with TurfHop using OpenAI Agents SDK?

You can retrieve details using getcustomer by ID. The MCP Server manages this lookup, and your agent just needs to know which tool to call.

Q: Can I list all historical quotes for billing purposes with TurfHop and OpenAI Agents SDK?

Yes. The listquotes tool pulls a complete rundown of all saved quotes. This information is critical when an agent needs to calculate revenue projections.

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Connect TurfHop MCP to OpenAI Agents SDK

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

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Automate Job and Customer Onboarding

The agent can handle the full lifecycle of a new service request. You pass customer data using `create_customer`, and then immediately schedule the work by calling `create_job`. This handles everything from initial contact to job setup. Because this MCP Server uses OpenAI Agents SDK's guardrails, your deployment system validates every action before it hits TurfHop. It keeps the workflow clean when setting up new records.

Review and Update Service Details

Need to adjust an existing job or client record? The agent uses `get_job` and `update_job` to pull up details, and then modifies them in one flow. This is great for field techs who need quick access to current service parameters. If a customer moves, you don't have to manually change everything. You just use `update_customer`, and the agent ensures that record matches your internal system’s expected format.

Generate Billing Reports from History

Retrieving financial summaries is straightforward. The client can call `list_invoices` to see all billing history, or use `get_invoice` for a deep dive on one specific bill. It also lets you check out what services are available via `list_products`. This entire process runs through the MCP Server, giving your AI agent the data it needs without requiring you to build custom database connectors.

Setup guide

Set up TurfHop 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 TurfHop tools at runtime.
3

Create your Agent

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

Run the agent

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

The OpenAI Agents SDK allows you to call `create_job` directly. You simply provide the necessary job data in a JSON string, and your agent handles passing that payload securely through the MCP Server.

You can retrieve details using `get_customer` by ID. The MCP Server manages this lookup, and your agent just needs to know which tool to call.

Yes. The `list_quotes` tool pulls a complete rundown of all saved quotes. This information is critical when an agent needs to calculate revenue projections.

This MCP Server handles invoice details and billing history via the `get_invoice` tool. You're dealing specifically with structured financial records that include dates and monetary values.

This MCP Server touches customer JSON strings, which contain personal identifying information. Your deployment must ensure the token used by your agent has restricted access only to necessary records.

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