How to Use the Miro (Visual Collaboration & Whiteboarding) MCP in OpenAI Agents SDK

Q: Can OpenAI Agents SDK handle multi-agent handoffs when editing boards using the Miro (Visual Collaboration & Whiteboarding) MCP Server?

Yes. You can configure one agent to run createboard and then hand off the session to a specialized layout agent that handles createshape and createstickynote. This keeps your agent logic modular and highly focused.

Q: Does this integration support reading existing board layouts?

Yes, this MCP Server exposes getboard and listboards to let your agent inspect existing structures. Your agent can read the current board list, select the correct ID, and analyze its contents before making modifications.

Build production-grade OpenAI Agents SDK workflows that directly generate Miro boards and sticky notes with built-in guardrails.

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Connect Miro (Visual Collaboration & Whiteboarding) MCP to OpenAI Agents SDK

Create your Vinkius account to connect Miro (Visual Collaboration & Whiteboarding) 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 Miro (Visual Collaboration & Whiteboarding) with OpenAI Agents SDK

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OpenAI Agents MCP Server Board Creation

The `create_board` tool spins up a new collaborative workspace directly from your Python runtime. When your agent detects a new project kickoff, it instantly triggers this tool to set up the canvas, bypass manual clicks, and establish a clean workspace. You get tracing through the OpenAI dashboard to monitor exactly when and how boards are initialized. This ensures your automated workflows stay organized without creating empty or orphaned canvases.

Automated Visual Retro Setup

The `create_sticky_note` tool places feedback elements onto your board to capture team insights automatically. Your agent uses this tool to map structured text from post-sprint logs into physical sticky notes, placing them at specific coordinates. By using the SDK's built-in guardrails, you ensure the agent never dumps duplicate notes onto the same coordinates. This keeps your retrospective boards clean and readable for the engineering team.

Team Audit and Tag Syncing

The `list_members` tool reads the active users on a board to audit access permissions dynamically. Your agent cross-references this list with your internal directory to flag unauthorized external emails. Combined with `list_tags`, this setup lets your agent categorize board elements based on who created them. You maintain complete control over board organization using this dedicated MCP Server without manually clicking through individual items.

Setup guide

Set up Miro (Visual Collaboration & Whiteboarding) 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 Miro (Visual Collaboration & Whiteboarding) tools at runtime.
3

Create your Agent

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

Run the agent

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

Install the SDK, then initialize the server stream using MCPServerStreamableHttp with the Vinkius endpoint. Pass this server instance directly inside the mcp_servers list when instantiating your Agent. The agent automatically discovers all eight Miro tools.

Yes. You can configure one agent to run create_board and then hand off the session to a specialized layout agent that handles create_shape and create_sticky_note. This keeps your agent logic modular and highly focused.

Use the OpenAI Agents SDK guardrails to set strict execution limits before calling create_sticky_note. You can also configure the agent to run list_items first to verify the current board density before adding more elements.

Yes, this MCP Server exposes get_board and list_boards to let your agent inspect existing structures. Your agent can read the current board list, select the correct ID, and analyze its contents before making modifications.

All board data, shape coordinates, sticky note text, and member emails are processed inside a secure, ephemeral V8 isolate sandbox. Your MCP credentials never leak, and no data is stored on Vinkius servers.

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