How to Use the YesNo MCP in OpenAI Agents SDK

Q: Does YesNo integrate with my OpenAI Agents SDK?

Yep. The MCP Server auto-discovers getdecision when you pass it into the Agent constructor. It works right out of the box.

Make instant yes/no decisions in your production OpenAI Agents SDK workflow.

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Connect YesNo MCP to OpenAI Agents SDK

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

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Randomly determine a choice

Your agent calls the `get_decision` tool to pull a random outcome. It returns 'yes', 'no', or 'maybe'—perfect for breaking ties in complex decision trees. This output includes an accompanying GIF, giving your AI client immediate visual context alongside the text result.

Force specific outcomes

Need the agent to commit? Use `get_decision` and pass a required answer. You can force 'yes' or 'no', regardless of what the random roll suggests. This mechanism lets you build guardrails into your agent, ensuring critical decisions always hit the intended state.

Quickly simulate choices

The `get_decision` tool simulates a quick vote or poll result. It provides simple 'yes/no' logic with minimal overhead. When building multi-step processes, this is the fastest way to get a binary input without hitting external APIs.

Setup guide

Set up YesNo 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 YesNo tools at runtime.
3

Create your Agent

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

Run the agent

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

Yep. The MCP Server auto-discovers `get_decision` when you pass it into the Agent constructor. It works right out of the box.

Absolutely. You just need to provide the desired value as an argument. This lets you override the random choice when your logic demands it.

It handles simple decision strings ('yes', 'no', 'maybe'). You'll see this type of text passed through your agent’s action logs.

Yes, since it exposes a simple, contained tool, it fits perfectly into an agent system built with guardrails. It's designed to be reliable and predictable.

Nah. The SDK auto-discovers the tool, meaning you just list the server endpoint. You don't need to write custom wrappers or handlers.

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