How to Use the Front MCP in OpenAI Agents SDK

Q: How do I connect Front to OpenAI Agents SDK?

Install the package with pip. Create an MCPServerStreamableHttp instance pointing to your Vinkius endpoint and pass it to your Agent constructor in the mcpservers list. Set cacheToolsList=True to speed up initialization.

Q: Can OpenAI Agents SDK hand off Front conversations between specialized agents?

Yes. You might build one agent that reads getconversationdetails and another that handles the actual reply. The SDK manages the handoff natively.

Build production-ready support agents with OpenAI Agents SDK and this MCP Server that read, route, and reply to Front shared inboxes.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect Front MCP to OpenAI Agents SDK

Create your Vinkius account to connect Front 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.

GDPR Free for Subscribers

Setup Front with OpenAI Agents SDK

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Route tickets with OpenAI Agents SDK

Your agent needs context before it acts. Call `search_conversations` to find related historical threads across your entire Front workspace. It hands that context to a specialized routing agent. That agent then fires `update_conversation_status` to assign the ticket to the right human or archive it. You get full tracing in the OpenAI dashboard to see exactly why it made that routing decision.

Draft and send replies safely

Support bots usually mess up because they lack boundaries. By connecting this MCP Server, your agent uses `list_conversation_messages` to read the exact thread history before drafting anything. Built-in guardrails validate the output. Once approved, the agent executes `send_inbox_reply` to dispatch the response directly to the customer. No manual copy-pasting required.

Map your team structure

Escalations require knowing who is available. The agent grabs your directory using `list_inbox_teammates` and checks `list_shared_inboxes` to understand your workspace setup. It matches the customer issue to the specific skills of a teammate. If it hits an error, `verify_api_status` runs a quick health check to ensure the connection remains stable.

Setup guide

Set up Front 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 Front tools at runtime.
3

Create your Agent

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

Run the agent

Call Runner.run(agent, prompt) to execute. The agent invokes the appropriate Front 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="Front Agent",
            instructions="You have access to Front tools.",
            mcp_servers=[server],
        )
        result = await Runner.run(agent, "List recent transactions")
        print(result.final_output)

asyncio.run(main())

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Front. 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.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect Front now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about Front MCP in OpenAI Agents SDK

Install the package with pip. Create an `MCPServerStreamableHttp` instance pointing to your Vinkius endpoint and pass it to your Agent constructor in the `mcp_servers` list. Set `cacheToolsList=True` to speed up initialization.

No. The SDK auto-discovers all 12 tools instantly. Your agent automatically knows how to call `list_address_book` or `get_inbox_details` without extra configuration.

Yes. You might build one agent that reads `get_conversation_details` and another that handles the actual reply. The SDK manages the handoff natively.

The agent receives a standard HTTP error. You configure retry logic or fallback constraints within the SDK to handle rate limits gracefully.

Vinkius runs the server in an ephemeral V8 Isolate Sandbox. Customer email bodies, contact details, and internal thread notes pass through a zero-trust tunnel directly to your client. We store absolutely nothing on disk.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript