How to Use the FieldAware MCP in OpenAI Agents SDK

Q: How do I connect the FieldAware MCP Server to my openai-agents-sdk setup?

Install openai-agents via pip and configure the MCPServerStreamableHttp parameter with your Vinkius endpoint. Pass the server instance directly to your agent constructor to auto-discover all twelve service management tools.

Q: Can an openai-agents-sdk agent create jobs in FieldAware?

Yes, the agent calls createjob using parameters it extracts from your customer communications. You can set strict schema validation within the SDK to ensure no required field is missing before execution.

Q: Does this FieldAware MCP Server integration support multi-agent handoffs in openai-agents-sdk?

Absolutely. Your triage agent can query listcustomers and then hand off the structured payload to a specialized dispatch agent that runs createjob.

Q: How does the agent handle inventory checks before dispatch?

The agent queries listitems to verify parts availability before scheduling. If an item is out of stock, the agent halts the dispatch sequence and alerts your team.

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Connect FieldAware MCP to OpenAI Agents SDK

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

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Automated dispatching via OpenAI Agents SDK

The `create_job` tool lets your OpenAI Agents SDK setup spin up work orders the moment a customer reports an issue. By pairing this with `list_jobs`, your OpenAI Agents SDK agent checks technician availability before scheduling, preventing double bookings on the fly. This python-driven integration uses the SDK's built-in guardrails to verify dispatch details before they hit your live FieldAware database. You define the safety rules, and the OpenAI Agents SDK executes the scheduling loops without human intervention.

Real-time customer and asset lookups

The `get_customer` tool pulls exact client profiles instantly when an OpenAI Agents SDK agent handles an incoming support ticket. Your agent then calls `list_assets` to match the customer's hardware history with their current service request. Because OpenAI Agents SDK handles multi-agent handoffs, a triage agent can gather this FieldAware data and pass it to a billing agent without losing context. The billing agent then uses `list_invoices` to check for unpaid balances before dispatching a technician.

Instant quote and invoice tracking

The `list_quotes` tool retrieves active estimates directly into your OpenAI Agents SDK workflow for immediate follow-up. When a customer approves a quote, the agent calls `get_invoice` to track the payment status in real time. This MCP Server connection ensures your autonomous OpenAI Agents SDK sales agent has direct access to financial records without manual exports. You get clean, structured data injected straight into your agent's decision-making loop.

Setup guide

Set up FieldAware 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 FieldAware tools at runtime.
3

Create your Agent

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

Run the agent

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

Install `openai-agents` via pip and configure the `MCPServerStreamableHttp` parameter with your Vinkius endpoint. Pass the server instance directly to your agent constructor to auto-discover all twelve service management tools.

Yes, the agent calls `create_job` using parameters it extracts from your customer communications. You can set strict schema validation within the SDK to ensure no required field is missing before execution.

Absolutely. Your triage agent can query `list_customers` and then hand off the structured payload to a specialized dispatch agent that runs `create_job`.

The agent queries `list_items` to verify parts availability before scheduling. If an item is out of stock, the agent halts the dispatch sequence and alerts your team.

Your jobs, invoices, and customer contact records stay inside the secure Vinkius V8 sandbox. The OpenAI Agents SDK communicates via ephemeral, token-authorized MCP streams, meaning your raw database is never exposed to public LLM training sets.

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