How to Use the Miro MCP in AutoGen

Q: Can an AutoGen agent audit Miro board members?

Yes, an agent can call listboardmembers to see who has access to a board. It can then debate with a security agent whether unauthorized users are present and flag any anomalies to you.

Q: How do I prevent AutoGen agents from deleting a Miro board?

You can configure your agent system so that the deleteboard tool requires multi-agent approval. This ensures no single agent can destroy a workspace without another agent verifying the request.

Deploy AutoGen agents with this Miro MCP Server to debate board layouts, agree on tasks, and place sticky notes.

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Create your Vinkius account to connect Miro 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.

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Setup Miro with AutoGen

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Let AutoGen agents debate board structures

The `create_board` tool gives your AutoGen agents a shared canvas to map out complex workflows. Before a single pixel is drawn, a product agent and a developer agent can debate the board's purpose and structure. Once they reach a consensus, the winning agent executes the board setup. This collaborative decision-making prevents messy, unorganized canvases and ensures every board has a clear, agreed-upon structure.

Coordinate sticky note placement

The `create_sticky_note` tool allows your agents to post their individual conclusions directly onto the board. One agent drafts the task details, another reviews it for technical accuracy, and a third places it on the canvas. This multi-agent review process ensures only high-quality, vetted ideas make it to your board. You avoid sticky note spam by forcing your agents to agree on the content before publishing.

Clean up workspaces via consensus

The `delete_board` tool is a high-stakes action that your AutoGen agents can guard with strict consensus rules. A performance agent might suggest removing an inactive board, but a compliance agent must verify the details first. By requiring multiple agents to sign off before invoking destructive tools, you protect your active workspaces from accidental deletion. It adds a reliable layer of safety to your automated canvas management.

Setup guide

Set up Miro 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 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_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

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

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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_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

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

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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.

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Common questions about Miro MCP in AutoGen

Your agents talk to each other to decide what needs to be built, then use tools like `create_sticky_note` to post their finalized ideas. This keeps the actual canvas clean and focused on agreed-upon concepts.

Yes, an agent can call `list_board_members` to see who has access to a board. It can then debate with a security agent whether unauthorized users are present and flag any anomalies to you.

You can configure your agent system so that the `delete_board` tool requires multi-agent approval. This ensures no single agent can destroy a workspace without another agent verifying the request.

Yes, the AutoGen MCP adapter automatically translates all 8 Miro tools into schemas your agents understand. This includes everything from listing organizations to pulling board details.

The server only touches board layouts, sticky notes, and member lists during active agent conversations. Vinkius runs the MCP Server in an ephemeral sandbox, meaning your private collaboration data is never saved or cached.

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