How to Use the Dime.Scheduler MCP in OpenAI Agents SDK

Deploy production-grade dispatch agents with OpenAI Agents SDK and real-time Dime.Scheduler ERP tracking.

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Connect Dime.Scheduler MCP to OpenAI Agents SDK

Create your Vinkius account to connect Dime.Scheduler 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 Dime.Scheduler with OpenAI Agents SDK

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Map field resources with native safety guardrails

This integration exposes the `list_resources` and `list_tasks` tools directly to your OpenAI agents. The SDK handles discovery instantly, letting your agent inspect active field technicians and pending work orders without manual API mapping. Because you are building for production, this MCP Server lets you set safety guardrails to verify resource assignments before they run. Your agent queries the current backlog, matches skills to tasks, and prepares the dispatch plan while you maintain absolute control over execution.

Run secure multi-agent handoffs for schedule conflicts

Conflict resolution relies on the `list_appointments` and `list_time_markers` tools to analyze the planning board. Setting up a multi-agent system lets one agent detect overlaps while another negotiates the reschedule. OpenAI's tracing dashboard records every single tool call and handoff. When an agent checks the planning board for blockages, you see the exact payload and execution path, making debugging straightforward and transparent.

Inspect job details using this MCP Server

Your agent pulls deep operational context using the `get_job`, `list_jobs`, and `list_categories` tools. This allows the model to look up specific work orders and retrieve their ERP-linked metadata on demand. Enabling the tool list cache ensures fast response times during high-frequency runs. The agent keeps the structural schema of your ERP jobs in memory, reducing latency when dispatching urgent field requests.

Setup guide

Set up Dime.Scheduler 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 Dime.Scheduler tools at runtime.
3

Create your Agent

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

Run the agent

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

Install the SDK with pip, then initialize the streamable HTTP transport pointing to your Vinkius endpoint. Pass the server instance inside the agent constructor's server list. Set the tool cache parameter to true to speed up repeated queries.

Yes, you can divide tasks between specialized agents. One agent can monitor incoming work orders using the job list tool, while a second agent handles resource matching using the resource list tool.

Yes, the SDK maintains active streaming channels to get live scheduling updates. Your agents always work with the latest planning board data without manual refreshes.

Use the native OpenAI developer dashboard to trace every execution step. You will see the exact arguments passed to the scheduling tools along with the raw response payloads from the ERP.

Your field service schedules and technician assignments stay inside your secure ERP environment and the Vinkius MCP Server runtime. No operational data is stored on Vinkius servers, and transport uses end-to-end encryption.

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