How to Use the Fairing MCP in OpenAI Agents SDK

Q: Is Fairing data cacheable within the OpenAI Agents SDK?

You can enable cacheToolsList in your configuration to speed up discovery. For actual survey data, it is better to query fresh results to keep your insights accurate.

Query zero-party data and automate customer insights directly within your OpenAI Agents SDK production environment.

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Connect Fairing MCP to OpenAI Agents SDK

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

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Trace customer intent with OpenAI Agents SDK

Your agent uses `get_customer_responses` to pull specific feedback linked to a buyer ID. It parses this input to identify churn signals before the next support ticket hits your queue. This MCP Server provides the raw data your agents need to build accurate customer profiles. By using `list_responses`, you feed structured sentiment directly into your agent's reasoning loop.

Monitor survey performance metrics

Call `get_insights` to visualize how your post-purchase questions perform across different segments. You get granular data without leaving your Python development flow. Your agent automatically retrieves these metrics to adjust its internal logic. It flags low-performing questions by checking `list_surveys` and comparing them against your current conversion benchmarks.

Manage your Fairing integration state

The `list_integrations` tool exposes exactly what services connect to your survey data. This ensures your agent is always aware of the data pipeline status. Verification happens via `get_me` to confirm the agent has the correct permissions. It keeps your security posture tight while maintaining full access to the necessary survey tools.

Setup guide

Set up Fairing 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 Fairing tools at runtime.
3

Create your Agent

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

Run the agent

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

You handle authentication through a single endpoint token managed by the Vinkius platform. This keeps your credentials out of your codebase while your OpenAI Agents SDK code interacts with the survey data.

Yes, but you should implement cursor-based pagination logic when calling `list_responses`. This ensures your agent processes data in manageable chunks without hitting API limits.

This server accesses zero-party survey responses, customer identifiers, and account metadata. It does not touch raw payment details or sensitive personal financial records.

No, the SDK automatically discovers all 12 tools upon connection. You simply pass the server instance to your agent, and it maps the functions to its execution context.

You can enable `cacheToolsList` in your configuration to speed up discovery. For actual survey data, it is better to query fresh results to keep your insights accurate.

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