How to Use the Miro MCP in CrewAI

Q: How do I add Miro to my CrewAI agents?

Pass the Vinkius URL directly into the mcps parameter of your Agent configuration. The crew will automatically gain access to the 8 available tools.

Q: Can CrewAI agents edit Miro boards?

Yes. Agents can invoke createstickynote to add content or deleteboard to manage workspace lifecycle, depending on the role you assign.

Deploy specialized agent crews to manage Miro boards with this autonomous Miro MCP Server.

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Connect Miro MCP to CrewAI

Create your Vinkius account to connect Miro to CrewAI 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 CrewAI

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Autonomous board management in CrewAI

Assign a dedicated agent to clean up or update boards using `delete_board` or `create_sticky_note`. It acts as part of your crew to keep the workspace tidy. You define the roles, and the agents handle the execution. It frees up your team to focus on the actual design work.

Collaborative research with CrewAI

Let your research agent scan existing content using `list_board_items`. It aggregates insights from the canvas for the rest of the crew to analyze. This creates a shared memory loop where agents build on each other's findings. Information flows between the board and your agents automatically.

Organize teams within CrewAI

Your moderator agent can use `list_board_members` to check who is active. It ensures the right people are involved in the current task. This prevents bottlenecks by identifying who is currently on the board. You gain visibility into your team's collaboration patterns.

Setup guide

Set up Miro MCP in CrewAI

Prerequisites

Python 3.10+ installed
crewai package (pip install crewai)
Active Vinkius subscription with a valid endpoint token

1

Install CrewAI
Run pip install crewai to install the framework. MCP support is built-in via the mcps parameter.
2

Add the MCP URL to your agent
Pass your Vinkius endpoint directly to the mcps list. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. CrewAI handles tool discovery and caching automatically.
3

Kick off your crew
Create a Crew with your agent and tasks. Call crew.kickoff() — the agent will automatically invoke Miro tools as needed.

crew.py

from crewai import Agent, Task, Crew

agent = Agent(
    role="Miro Analyst",
    goal="Access and analyze Miro data via MCP.",
    backstory="Expert analyst with direct Miro access.",
    mcps=[
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ],
)

task = Task(
    description="List recent Miro transactions",
    agent=agent,
    expected_output="A summary of recent activity",
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

Get your connection token →

Prerequisites

Python 3.10+ installed
crewai + crewai-tools packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install crewai crewai-tools. The MCPServerAdapter handles lifecycle management and tool conversion.
2

Connect with MCPServerAdapter
Use MCPServerAdapter as a context manager with SseServerParameters pointing to your Vinkius endpoint. The adapter automatically manages connection lifecycle.
3

Assign tools and run
Pass the returned mcp_tools to your agent's tools parameter. The adapter converts MCP tools to native BaseTool objects compatible with all CrewAI agents.

crew.py

from crewai import Agent, Task, Crew
from crewai_tools import MCPServerAdapter
from mcp import SseServerParameters

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

with MCPServerAdapter(server_params) as mcp_tools:
    agent = Agent(
        role="Miro Analyst",
        goal="Access and analyze Miro data via MCP.",
        backstory="Expert analyst with direct Miro access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent Miro transactions",
        agent=agent,
        expected_output="A summary of recent activity",
    )

    crew = Crew(agents=[agent], tasks=[task])
    result = crew.kickoff()
    print(result)

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.

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Common questions about Miro MCP in CrewAI

Pass the Vinkius URL directly into the `mcps` parameter of your Agent configuration. The crew will automatically gain access to the 8 available tools.

Yes. Agents can invoke `create_sticky_note` to add content or `delete_board` to manage workspace lifecycle, depending on the role you assign.

The MCP server allows agents to fetch board data. You can pipe this data into your agent's shared memory for collaborative tasks.

The server uses strict ephemeral connections. Your board data is processed only during the agent's execution and never persisted on Vinkius.

Use the tool filter in your MCP client configuration. You can restrict specific agents to only read data while others handle creation.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.