How to Use the Dixa MCP in OpenAI Agents SDK

Q: How do I connect the Dixa MCP Server to my OpenAI Agents SDK pipeline?

Install openai-agents and initialize MCPServerStreamableHttp with your Vinkius endpoint. Pass this server instance in the mcpservers list when instantiating your Agent, and the SDK automatically discovers all ten tools.

Q: Can my OpenAI Agents SDK agent assign Dixa tickets based on team membership?

Yes. Your agent calls listsupportteams to see who is online and then uses getagentprofile to check their specific skills. The OpenAI Agents SDK manages these tool calls sequentially during the run loop.

Q: How does the Dixa integration handle API rate limits within the OpenAI Agents SDK?

The server exposes getserviceaccountmetadata so your agent can monitor your current Dixa rate limits. You can write a custom guardrail in the SDK to pause tool execution if you approach these thresholds.

Q: Can I search conversations by subject line?

Yes, the searchconversationsbysubject tool allows your agent to locate specific historical threads. It runs keyword searches directly against your support database to find matching customer records.

Run production-ready Dixa support agents with built-in guardrails using the OpenAI Agents SDK.

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Connect Dixa MCP to OpenAI Agents SDK

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

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Perplexity

Control Dixa queues with OpenAI Agents SDK safety

`list_service_queues` lets your OpenAI Agents SDK agent pull active support channels directly into your run loop. The agent inspects live queue loads and routes incoming requests without manual dispatching. This MCP Server integration ensures your agent checks `list_open_support_tickets` before pushing new work to agents. By combining these checks with OpenAI's built-in guardrails, you prevent your code from overloading active queues when ticket spikes hit.

Audit support team availability in real time

`quick_agent_presence_audit` exposes live agent statuses directly to your Python execution context. Your agent uses this data to decide whether to assign a ticket or hold it in the queue. If an agent goes offline, this MCP tool handles the state change and uses `get_agent_profile` to find an available backup in the same tier. This keeps customer conversations moving without relying on flaky, hardcoded routing tables.

Inspect customer histories automatically

`list_customer_conversations` fetches the entire interaction history for any customer identifier your agent encounters. Your OpenAI Agents SDK agent parses these past threads to extract context before replying. When the agent needs specific details, it runs `get_conversation_details` to read internal notes or previous resolutions. You get clean context injection into your prompt window without writing custom database connectors.

Setup guide

Set up Dixa 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 Dixa tools at runtime.
3

Create your Agent

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

Run the agent

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

Install `openai-agents` and initialize `MCPServerStreamableHttp` with your Vinkius endpoint. Pass this server instance in the `mcp_servers` list when instantiating your Agent, and the SDK automatically discovers all ten tools.

Yes. Your agent calls `list_support_teams` to see who is online and then uses `get_agent_profile` to check their specific skills. The OpenAI Agents SDK manages these tool calls sequentially during the run loop.

The server exposes `get_service_account_metadata` so your agent can monitor your current Dixa rate limits. You can write a custom guardrail in the SDK to pause tool execution if you approach these thresholds.

Yes, the `search_conversations_by_subject` tool allows your agent to locate specific historical threads. It runs keyword searches directly against your support database to find matching customer records.

All data transit happens inside an isolated V8 sandbox on Vinkius, meaning your Dixa conversation details and agent profiles are never stored. The OpenAI Agents SDK communicates with the server via encrypted HTTP streams, preventing exposure of sensitive support tickets.

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