How to Use the MaestroQA MCP in OpenAI Agents SDK

Q: How do I handle slow exports with MaestroQA and OpenAI Agents SDK?

Set cacheToolsList=True for better performance and run your export tasks asynchronously. Your agent initiates the process with requestqadataexport and can execute other tasks while waiting. It then fetches the results using getexportdownloadlinks once the platform finishes compiling the data.

Connect MaestroQA to your OpenAI Agents SDK pipelines to automate QA audits with strict guardrails and real-time tracing.

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Connect MaestroQA MCP to OpenAI Agents SDK

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

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Run automated QA audits with OpenAI Agents SDK

This MCP Server exposes `list_qa_tickets` and `get_ticket_qa_details` so your agent can inspect support quality metrics directly. By passing this server to your agent constructor, your pipeline automatically discovers these tools without manual API mapping. Your production agent can pull raw data, inspect specific grading rubrics with `list_qa_rubrics`, and flag underperforming tickets. This means your QA team only looks at the edge cases that actually need human eyes.

Sync CSAT scores back to MaestroQA safely

Your agent uses `push_csat_scores` to sync calculated customer satisfaction metrics back to your QA platform. OpenAI's built-in guardrails validate agent actions before they write back to your production systems, protecting your historical records. If a score looks off or fails your custom safety checks, the agent pauses execution or hands off the task to a supervisor agent. This keeps your quality data clean and reliable.

Manage bulk exports with async agent pipelines

The `request_qa_data_export` tool starts an asynchronous bulk data export that your agent tracks to completion. Pulling months of support history takes time, which is why your agent handles these exports in the background. Once the export finishes, the agent grabs the secure files with `get_export_download_links` and prepares them for analysis. You can trace this entire multi-step process directly inside the OpenAI dashboard to debug failures instantly.

Setup guide

Set up MaestroQA 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 MaestroQA tools at runtime.
3

Create your Agent

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

Run the agent

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

The SDK handles discovery automatically when you pass the server context to your agent. You initialize the connection using `MCPServerStreamableHttp` and register it in the `mcp_servers` list. Your agent instantly knows how to call tools like `list_qa_agents` without manual configuration.

Yes, you can control tool access using the SDK's built-in guardrails and system instructions. While this MCP Server exposes all seven tools, you can instruct the agent to only read data using `list_qa_tickets` and block any write actions. This keeps your quality assurance data safe from unauthorized changes.

Set `cacheToolsList=True` for better performance and run your export tasks asynchronously. Your agent initiates the process with `request_qa_data_export` and can execute other tasks while waiting. It then fetches the results using `get_export_download_links` once the platform finishes compiling the data.

Absolutely, you can set up a triage agent that scans tickets using `list_qa_tickets` and hands off the actual review to a specialized grading agent. The grading agent then pulls specific details using `get_ticket_qa_details` to complete the audit.

Vinkius runs the server in an isolated V8 sandbox, ensuring your API keys never leak. The server only handles the specific QA reviews, rubric structures, and agent scores required for your queries. No data is stored on Vinkius servers, and all traffic is encrypted end-to-end via an ephemeral MCP connection.

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