How to Use the ChatFly MCP in OpenAI Agents SDK

Q: Can I list ChatFly bots inside an OpenAI Agents SDK loop?

You can absolutely pull the full bot registry using the listbots tool. It returns a clean list that your agent can parse to decide which bot handles the current user request.

Q: Is it easy to change bot data in OpenAI Agents SDK?

Use updatebot to push changes to your existing bots. It is a direct tool call that reflects in the ChatFly environment immediately.

Deploy ChatFly bots directly into your OpenAI Agents SDK production pipeline for automated lead qualification and scheduling.

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Connect ChatFly MCP to OpenAI Agents SDK

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

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Automated bot deployment in OpenAI Agents SDK

Call `create_bot` to spin up new instances directly from your Python agent code. You define the welcome message and bot name on the fly. This MCP Server handles the backend logic so your agent focuses on the conversation flow. Your agent keeps its state clean while managing multiple bots.

Data-driven responses for OpenAI Agents SDK

Inject specific knowledge by using `upload_data_source` to feed documents into your bots. Your agent triggers this whenever new customer info arrives. The `list_data_sources` tool lets your agent check what the bot already knows. It prevents redundant uploads and keeps your knowledge base precise.

Real-time bot management for OpenAI Agents SDK

Query your live fleet using `list_bots` and `get_bot` to monitor performance metrics. The agent pulls current status data without manual intervention. Updating bot settings happens instantly with `update_bot`. Your agent modifies parameters based on changing customer needs or new product details.

Setup guide

Set up ChatFly 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 ChatFly tools at runtime.
3

Create your Agent

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

Run the agent

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

asyncio.run(main())

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Common questions about ChatFly MCP in OpenAI Agents SDK

Use the MCPServerStreamableHttp class to point your agent at the Vinkius endpoint. The SDK automatically picks up the available tools, letting you call bot functions in your async loops.

Yes. Since the SDK validates every action, you can wrap the bot tools in your existing safety logic. This prevents the bot from making unauthorized updates to your customer data.

You can absolutely pull the full bot registry using the `list_bots` tool. It returns a clean list that your agent can parse to decide which bot handles the current user request.

Use `update_bot` to push changes to your existing bots. It is a direct tool call that reflects in the ChatFly environment immediately.

We store your bot credentials securely at the endpoint level. The data payloads sent through the MCP protocol never touch your agent's private memory, keeping your customer interactions isolated.

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