How to Use the Zendesk QA (Klaus) MCP in OpenAI Agents SDK

Q: How do I find all the available workspaces using Zendesk QA (Klaus) and OpenAI Agents SDK?

You call the listqaworkspaces tool. It returns a list of IDs, which you then feed into other tools to narrow your focus. This step is necessary before listing reviews for any specific area.

Q: Does Zendesk QA (Klaus) and OpenAI Agents SDK support deleting old ticket data?

Yes, the deleteqatickets tool handles this cleanup. You can remove specific tickets from the QA platform when you're done with them or need to comply with retention policies.

Q: What process should I follow for reviewing a single department using Zendesk QA (Klaus) and OpenAI Agents SDK?

First, use listqaworkspaces to get the ID. Then, pass that ID into listworkspacereviews. That gives you all the quality reviews specific to that one workspace.

Q: If I need to search for old conversations with Zendesk QA (Klaus) and OpenAI Agents SDK, which tool should I use?

You'll use searchqaconversations. This function lets your agent query the platform by keywords or date range. It’s much better than browsing manually.

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Connect Zendesk QA (Klaus) MCP to OpenAI Agents SDK

Create your Vinkius account to connect Zendesk QA (Klaus) 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 Zendesk QA (Klaus) with OpenAI Agents SDK

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Gathering Account-Wide Quality Reviews

The `list_all_reviews` tool gathers every quality assurance review across your accounts. You can see a summary of all recorded QA activity in one place, making it easy to check overall team performance. Need reviews for a specific department? Use `list_qa_workspaces` first. It identifies the necessary workspace IDs, letting you run `list_workspace_reviews` for focused reporting.

Searching Past Conversations

Run `search_qa_conversations` to pinpoint specific discussions within Zendesk QA. You'll find conversations based on keywords or date ranges, which is crucial when tracking down a particular incident. Agents use this search tool to narrow down vast amounts of conversational data quickly. It doesn't just list titles; it gives you the context needed to understand what happened.

Syncing Users and Importing Tickets

The MCP Server lets your agent handle user management with `import_qa_users`, keeping agents and managers synced across systems. If you need a clean slate, the `delete_qa_tickets` tool removes specific ticket data directly from the QA platform. Furthermore, use `import_qa_tickets` to push new conversation data into Zendesk QA for immediate review. It’s fast setup for getting your raw support data ready for analysis.

Setup guide

Set up Zendesk QA (Klaus) 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 Zendesk QA (Klaus) tools at runtime.
3

Create your Agent

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

Run the agent

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

You call the `list_qa_workspaces` tool. It returns a list of IDs, which you then feed into other tools to narrow your focus. This step is necessary before listing reviews for any specific area.

Yes, the `delete_qa_tickets` tool handles this cleanup. You can remove specific tickets from the QA platform when you're done with them or need to comply with retention policies.

First, use `list_qa_workspaces` to get the ID. Then, pass that ID into `list_workspace_reviews`. That gives you all the quality reviews specific to that one workspace.

The server touches ticket data, user records, and review metrics. Your agent can manage the import, deletion, and listing of all these core pieces of information.

You'll use `search_qa_conversations`. This function lets your agent query the platform by keywords or date range. It’s much better than browsing manually.

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