How to Use the Certify (Emburse) MCP in OpenAI Agents SDK

Get your OpenAI Agents SDK codebase auditing and pulling Certify (Emburse) expense reports on autopilot.

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Connect Certify (Emburse) MCP to OpenAI Agents SDK

Create your Vinkius account to connect Certify (Emburse) 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 Certify (Emburse) with OpenAI Agents SDK

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Map GL dimensions inside OpenAI Agents SDK

The `get_gl_dimensions` tool exposes your entire General Ledger structure to your running OpenAI python agent. This setup lets your guardrailed agents verify that transactions match your accounting rules before they trigger downstream pipeline handoffs. You configure the agent with this MCP Server using MCPServerStreamableHttp to auto-discover this tool. This ensures your production code pulls live accounting categories instead of relying on outdated hardcoded lists.

Audit employee spend with this MCP Server

This MCP Server exposes `list_certify_expenses` and `list_expense_reports` to track where your company cash is actually going. Your agent runs these tools to pull raw lines and flag policy violations in real-time. Tracing in the OpenAI dashboard shows you exactly when and why the agent fetched these records. This transparency keeps your automated audits auditable by human finance teams.

Match receipts to invoices automatically

The `list_certify_receipts` tool works alongside `list_certify_invoices` to pair documentation with pending payables. Your specialized agent checks the invoice details against the raw receipt image data. Setting cacheToolsList to true keeps your API latency low during high-volume batch matching runs. The agent handles the handoff between matching and flagging without dropping connections.

Setup guide

Set up Certify (Emburse) 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 Certify (Emburse) tools at runtime.
3

Create your Agent

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

Run the agent

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

Install the SDK and pass the server URL to MCPServerStreamableHttp inside your agent's server list. The agent auto-discovers all eight tools instantly.

Yes, you can configure your OpenAI Agents SDK to hand off tasks between specialized agents. One agent can pull invoice reports while another audits departments.

It does, and you should set cacheToolsList to true in your configuration. This prevents the SDK from querying the server schema on every single agent turn.

Use the OpenAI developer dashboard to trace every call to Certify tools like `list_certify_users`. You see the exact payload sent and the JSON returned.

All invoice reports and expense lines stay sandboxed within Vinkius V8 isolates. Your credentials never leak to the LLM, and data is only fetched via ephemeral, encrypted connections.

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