How to Use the Miro (Visual Collaboration & Whiteboarding) MCP in AutoGen

Let your AutoGen agents debate board layouts and coordinate task creation directly on your Miro canvas.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect Miro (Visual Collaboration & Whiteboarding) MCP to AutoGen

Create your Vinkius account to connect Miro (Visual Collaboration & Whiteboarding) to AutoGen 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 Miro (Visual Collaboration & Whiteboarding) with AutoGen

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Debate and Design via AutoGen MCP Server

The Miro MCP Server lets your AutoGen agents coordinate visual layouts by calling `create_board` to start a project. One agent acts as the designer while another reviews the layout. They debate the structure before executing `create_shape` to group different workflow zones. This consensus-driven approach prevents board clutter and ensures clean designs.

Collaborative Sticky Population

The Miro MCP Server allows your AutoGen writing agent to call `create_sticky_note` and place cards on the canvas. Your editor agent reviews the text beforehand. Another agent can then run `list_tags` to verify the organization. If a tag is missing, the agents discuss what label fits best and apply it, keeping the workspace organized.

Automated Board Reviews and Audits

The Miro MCP Server enables your auditing agent to call `list_items` to pull everything on the canvas. A project manager agent simultaneously checks `list_members` to see who is active. They compare the board state using `get_board` against your internal project trackers. If they find discrepancies, they highlight them in their chat log or generate a clean-up plan.

Setup guide

Set up Miro (Visual Collaboration & Whiteboarding) MCP in AutoGen

Prerequisites

Python 3.10+ installed
autogen-ext[mcp] package
Active Vinkius subscription with a valid endpoint token

1

Install AutoGen with MCP
Run pip install "autogen-ext[mcp]" autogen-agentchat. The MCP extension includes mcp_server_tools for stateless tool access.
2

Fetch tools from the MCP
Call mcp_server_tools(SseServerParams(url=...)) with your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Run your agent
Pass the tools to AssistantAgent and call agent.run(). The agent invokes Miro (Visual Collaboration & Whiteboarding) tools and returns structured results.

agent.py

from autogen_ext.tools.mcp import SseServerParams, mcp_server_tools
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

server_params = SseServerParams(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

tools = await mcp_server_tools(server_params)

agent = AssistantAgent(
    name="Miro (Visual Collaboration & Whiteboarding)_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent Miro (Visual Collaboration & Whiteboarding) data")
print(result.messages[-1].content)

Get your connection token →

Prerequisites

Python 3.10+ installed
autogen-ext[mcp] + autogen-agentchat
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Same packages as above. McpWorkbench is ideal when your agent needs stateful sessions across multiple tool calls.
2

Use McpWorkbench as context manager
Wrap your agent in async with McpWorkbench(...) to maintain shared state and resources. The workbench manages the full MCP session lifecycle.
3

Run with workbench
Pass workbench=workbench to your agent. State is preserved across multiple tool calls within the same session.

agent.py

from autogen_ext.tools.mcp import McpWorkbench, SseServerParams
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

server_params = SseServerParams(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

async with McpWorkbench(server_params) as workbench:
    agent = AssistantAgent(
        name="Miro (Visual Collaboration & Whiteboarding)_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent Miro (Visual Collaboration & Whiteboarding) data")
    print(result.messages[-1].content)

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 Miro. 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 Miro (Visual Collaboration & Whiteboarding) 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 Miro (Visual Collaboration & Whiteboarding) MCP in AutoGen

Use the autogen-ext package and wrap the MCP server using mcp_server_tools. Pass the resulting tool list directly into your AssistantAgent constructor.

Yes. Since the tools are stateless, multiple agents in your group chat can call `create_sticky_note` or `list_items` in parallel during their conversation.

The MCP adapter translates Miro errors into clear tool responses. Your agents read these errors, discuss the issue in their chat, and adjust their parameters before trying `create_board` again.

Yes, the Vinkius platform manages the HTTP connection, and the AutoGen MCP extension handles the schema conversion automatically for clean integration.

Your Miro credentials and board item details are handled through secure environment variables. Vinkius executes the code in isolated, ephemeral sandboxes, ensuring your board members' data never leaks.

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