How to Use the WorkflowMax MCP in OpenAI Agents SDK

Q: How does WorkflowMax and OpenAI Agents SDK handle new client creation?

Your agent calls createclient to make a new record. This immediately establishes the unique Client UUID required for all subsequent operations.

Q: Can I list all active jobs using WorkflowMax and OpenAI Agents SDK?

Yes, the listjobs tool pulls an overview of every project currently tracked on the MCP Server. It's perfect for quickly seeing which projects need attention.

Q: What is the best way to audit time logs with WorkflowMax and OpenAI Agents SDK?

Use the listtimesheets tool. This gathers all timesheet entries across different jobs, letting you see exactly who worked on what and for how long.

Q: Does this MCP Server handle task units?

Absolutely. The listtasks tool lists all service unit types that can be assigned to a job, ensuring your timesheets are always specific.

Q: If I need client data validation, what does WorkflowMax and OpenAI Agents SDK provide?

The agent uses getclient or getclientcontact to fetch data. Because the process is running in a production context, you get reliable, structured responses.

Manage jobs and contacts using your OpenAI Agents SDK.

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Connect WorkflowMax MCP to OpenAI Agents SDK

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

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Managing Client Accounts with WorkflowMax MCP Server

The `create_client` tool lets your agent establish a new company or individual client record. You pass the name, and the system handles the initial account setup. Need to add contacts? The `create_client_contact` function uses an existing Client UUID to append specific details for that person, keeping all records together.

Tracking Time with WorkflowMax MCP Server

The agent calls `create_timesheet` when work is done. You simply supply the Job UUID, Task UUID, and how many hours were spent. Don't forget to verify the time entries. The `list_timesheets` tool gives a clear overview of all logged time, making auditing simple.

Project Oversight with WorkflowMax MCP Server

Getting an overall view is easy. Use `list_jobs` to pull together every active project managed by the server. This shows you exactly which client and start date are linked. Need to adjust a scope? The `update_job` tool lets your agent modify existing job details, keeping the records current without needing manual database edits.

Setup guide

Set up WorkflowMax 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 WorkflowMax tools at runtime.
3

Create your Agent

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

Run the agent

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

Your agent calls `create_client` to make a new record. This immediately establishes the unique Client UUID required for all subsequent operations.

Yes, the `list_jobs` tool pulls an overview of every project currently tracked on the MCP Server. It's perfect for quickly seeing which projects need attention.

Use the `list_timesheets` tool. This gathers all timesheet entries across different jobs, letting you see exactly who worked on what and for how long.

Absolutely. The `list_tasks` tool lists all service unit types that can be assigned to a job, ensuring your timesheets are always specific.

The agent uses `get_client` or `get_client_contact` to fetch data. Because the process is running in a production context, you get reliable, structured responses.

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