How to Use the JobProgress (Leap) MCP in OpenAI Agents SDK

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Connect JobProgress (Leap) MCP to OpenAI Agents SDK

Create your Vinkius account to connect JobProgress (Leap) 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 JobProgress (Leap) with OpenAI Agents SDK

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Sync pipelines directly using this MCP Server

The `list_jobs` tool gives your agents instant visibility into active contractor projects and their current stages. This tool connects your automated triage agents directly to live construction pipelines without manual database exports. Your OpenAI Agents SDK agents can automatically trigger downstream workflows when a status changes. By calling `get_job`, the agent inspects specific cost estimates and updates the team via Slack when a milestone is met.

Pre-populate estimates with customer history

Before drafting any proposal, your agents use `get_customer` to pull historical addresses and custom metadata. This prevents your team from bidding on projects without knowing a client's past payment or project history. By combining `list_customers` with specific search terms, your agents quickly locate active accounts. The agent validates this data against your internal records before executing any client-facing actions.

Coordinate field calendars with built-in safety

The `list_appointments` tool lets your agents scan the field service calendar to prevent scheduling conflicts. Because the OpenAI Agents SDK enforces runtime guardrails, your agent won't book overlapping times. To keep crews on track, the agent uses `list_tasks` and `list_workflows` to map out daily checklists. If a task stalls, the agent automatically flags the assigned supervisor found via `list_users`.

Setup guide

Set up JobProgress (Leap) 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 JobProgress (Leap) tools at runtime.
3

Create your Agent

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

Run the agent

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

Install the SDK and spin up the MCP server using the HTTP transport. Register the server URL in your agent's configuration, and the agent will auto-discover tools like list_jobs and get_customer instantly.

Yes, the SDK handles concurrent tool execution. If your agent needs to audit sales performance, it can call list_estimates and list_proposals at the same time to compile a quick conversion report.

The SDK catches transport-level errors when a tool call fails. You should manage token refreshes at your middleware layer so the server keeps responding to list_tasks calls without interrupting your active agents.

You can filter the exposed tool list during agent initialization. If you only want an agent to read schedules, pass only list_appointments and list_users to the agent constructor.

Your project budgets, customer contact details, and workflow schedules stay inside your secure environment. This MCP Server runs in a sandboxed V8 isolate, meaning no customer data is stored or logged externally.

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