How to Use the Fera.ai MCP in OpenAI Agents SDK

Q: Can my OpenAI Agents SDK setup filter reviews before displaying them using Fera.ai?

Yes. Your agent can call listreviews to fetch recent submissions and analyze the text. Based on the rating or sentiment, the agent can decide whether to queue the review for your site.

Q: Does the Fera.ai integration with OpenAI Agents SDK support multiple store locations?

It does. The agent can invoke liststores to see all managed storefronts under your account. From there, it targets specific reviews or ratings by passing the correct store identifier.

Q: How does this MCP Server handle the privacy of customer review data?

All customer feedback and PII retrieved via getcustomer stays within your sandboxed execution context. Vinkius runs the server in an isolated environment, meaning your API keys and raw review payloads are never cached or exposed to third parties.

Feed live Fera.ai product ratings and customer reviews directly into your OpenAI Agents SDK pipelines with this MCP Server.

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Connect Fera.ai MCP to OpenAI Agents SDK

Create your Vinkius account to connect Fera.ai 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 Fera.ai with OpenAI Agents SDK

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Run automated Fera.ai social proof audits

Your agent uses `get_product_rating` and `list_reviews` to pull real-time Fera.ai customer feedback. It checks what buyers actually think about a specific SKU before making decisions. The OpenAI Agents SDK runs these Fera.ai tools with built-in guardrails. This means your agent won't accidentally push negative reviews or broken rating data to your storefront.

Track Fera.ai customer sentiment profiles

Look up who is leaving feedback by calling `list_customers` and `get_customer`. Your agent matches specific Fera.ai reviews to actual buyer profiles to find your brand champions. This MCP Server exposes raw buyer history to your OpenAI pipeline. You can route high-value customer details straight to your support agents when a bad Fera.ai review pops up.

Monitor Fera.ai visual user-generated content

Customers post photos and videos of your products. Your agent uses `list_media` to fetch these Fera.ai assets and verify they look good. It can also run `list_site_content` to see where these Fera.ai photos are currently showing up on your store. This keeps your visual social proof fresh without manual folder searching.

Setup guide

Set up Fera.ai 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 Fera.ai tools at runtime.
3

Create your Agent

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

Run the agent

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

Install the SDK and use the MCPServerStreamableHttp class to connect to the Vinkius endpoint. Pass the server instance directly into your Agent constructor's mcp_servers list. Your agents will discover the tools automatically.

Yes. Your agent can call list_reviews to fetch recent submissions and analyze the text. Based on the rating or sentiment, the agent can decide whether to queue the review for your site.

It does. The agent can invoke list_stores to see all managed storefronts under your account. From there, it targets specific reviews or ratings by passing the correct store identifier.

Set cacheToolsList=True in your SDK configuration. This prevents your agent from querying the server structure on every single run, which speeds up response times significantly.

All customer feedback and PII retrieved via get_customer stays within your sandboxed execution context. Vinkius runs the server in an isolated environment, meaning your API keys and raw review payloads are never cached or exposed to third parties.

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