Can I list all items on a Miro board using my AI agent?

Yes! Use the `list_board_items` tool and provide the Board ID. Your agent will retrieve all widgets, sticky notes, and text blocks on that board.

How do I add a new sticky note to a board?

Use the `create_sticky_note` action. Provide the Board ID and the content of your note to place it programmatically on the whiteboard.

Is it possible to manage board members via AI?

Yes, the `get_board_members` tool allows you to retrieve a list of all users who have access to a specific board, along with their roles.

INSTANT PLUG AND PLAY

Miro MCP Server for CrewAIGive CrewAI instant access to 8 tools to Create Board, Create Sticky Note, Delete Board, and more

Name: Miro
Availability: InStock
Author: Vinkius

Built by Vinkius GDPR 8 Tools Framework

Connect your CrewAI agents to Miro through Vinkius, pass the Edge URL in the `mcps` parameter and every Miro tool is auto-discovered at runtime. No credentials to manage, no infrastructure to maintain.

Use with Your AI Agent

Ask AI about this App Connector for CrewAI

Open in ChatGPT Open in Claude Open in Perplexity

The Miro app connector for CrewAI is a standout in the Industry Titans category — giving your AI agent 8 tools to work with, ready to go from day one.

Vinkius delivers Streamable HTTP and SSE to any MCP client

python

from crewai import Agent, Task, Crew

agent = Agent(
    role="Miro Specialist",
    goal="Help users interact with Miro effectively",
    backstory=(
        "You are an expert at leveraging Miro tools "
        "for automation and data analysis."
    ),
    # Your Vinkius token. get it at cloud.vinkius.com
    mcps=["https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"],
)

task = Task(
    description=(
        "Explore all available tools in Miro "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 8 available tools "
        "and what they can do."
    ),
)

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

Fully ManagedVinkius Servers

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IAMAccess control

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Ed25519Audit chain

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Stream every event to Splunk, Datadog, or your own webhook in real-time

* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About Miro MCP Server

Connect your Miro account to any AI agent and simplify your visual collaboration and whiteboarding workflows through natural conversation.

When paired with CrewAI, Miro becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Miro tools autonomously, one agent queries data, another analyzes results, a third compiles reports, all orchestrated through Vinkius with zero configuration overhead.

What you can do

Board Management — List all collaborative boards, retrieve detailed metadata, and create new boards programmatically
Visual Content Control — List all items on a board (sticky notes, shapes, text) and place new content directly from your agent
Member Coordination — Query board members and sharing settings to manage access across your organization
Operational tracking — Monitor board activity and stay on top of your visual projects
Direct Whiteboarding — Add sticky notes and ideas to a board without leaving your conversation

The Miro MCP Server exposes 8 tools through the Vinkius. Connect it to CrewAI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

All 8 Miro tools available for CrewAI

When CrewAI connects to Miro through Vinkius, your AI agent gets direct access to every tool listed below — spanning whiteboarding, visual-collaboration, brainstorming, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.

create_board

Create a new Miro board

create_sticky_note

Add a sticky note to a board

delete_board

Delete a Miro board

get_board_details

Get details for a specific board

list_board_items

List all items on a board

list_board_members

List board collaborators

list_boards

List Miro boards

list_organizations

List linked organizations

Connect Miro to CrewAI via MCP

Follow these steps to wire Miro into CrewAI. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.

Install CrewAI

Run pip install crewai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com

Customize the agent

Adjust the role, goal, and backstory to fit your use case

Run the crew

Run python crew.py. CrewAI auto-discovers 8 tools from Miro

Why Use CrewAI with the Miro MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with Miro through the Model Context Protocol.

Multi-agent collaboration lets you decompose complex workflows into specialized roles, one agent researches, another analyzes, a third generates reports, each with access to MCP tools

CrewAI's native MCP integration requires zero adapter code: pass Vinkius Edge URL directly in the `mcps` parameter and agents auto-discover every available tool at runtime

Built-in task delegation and shared memory mean agents can pass context between steps without manual state management, enabling multi-hop reasoning across tool calls

Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports

Miro + CrewAI Use Cases

Practical scenarios where CrewAI combined with the Miro MCP Server delivers measurable value.

Automated multi-step research: a reconnaissance agent queries Miro for raw data, then a second analyst agent cross-references findings and flags anomalies. all without human handoff

Scheduled intelligence reports: set up a crew that periodically queries Miro, analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain Miro tools with other MCP servers in the same crew, letting agents correlate data across multiple providers in a single workflow

Compliance and audit automation: a compliance agent queries Miro against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

Example Prompts for Miro in CrewAI

Ready-to-use prompts you can give your CrewAI agent to start working with Miro immediately.

"List all boards in my Miro account."

"Add a sticky note with 'Implement SSO' to the 'Engineering' board."

"Who has access to the 'Confidential Strategy' board?"

Troubleshooting Miro MCP Server with CrewAI

Common issues when connecting Miro to CrewAI through the Vinkius, and how to resolve them.

MCP tools not discovered

Ensure the Edge URL is correct. CrewAI connects lazily when the crew starts. check console output.

Agent not using tools

Make the task description specific. Instead of "do something", say "Use the available tools to list contacts".

Timeout errors

CrewAI has a 10s connection timeout by default. Ensure your network can reach the Edge URL.

Rate limiting or 429 errors

Vinkius enforces per-token rate limits. Check your subscription tier and request quota in the dashboard. Upgrade if you need higher throughput.

Miro + CrewAI FAQ

Common questions about integrating Miro MCP Server with CrewAI.

How does CrewAI discover and connect to MCP tools?

CrewAI connects to MCP servers lazily. when the crew starts, each agent resolves its MCP URLs and fetches the tool catalog via the standard tools/list method. This means tools are always fresh and reflect the server's current capabilities. No tool schemas need to be hardcoded.

Can different agents in the same crew use different MCP servers?

Yes. Each agent has its own mcps list, so you can assign specific servers to specific roles. For example, a reconnaissance agent might use a domain intelligence server while an analysis agent uses a vulnerability database server.

What happens when an MCP tool call fails during a crew run?

CrewAI wraps tool failures as context for the agent. The LLM receives the error message and can decide to retry with different parameters, fall back to a different tool, or mark the task as partially complete. This resilience is critical for production workflows.

Can CrewAI agents call multiple MCP tools in parallel?

CrewAI agents execute tool calls sequentially within a single reasoning step. However, you can run multiple agents in parallel using process=Process.parallel, each calling different MCP tools concurrently. This is ideal for workflows where separate data sources need to be queried simultaneously.

Can I run CrewAI crews on a schedule (cron)?

Yes. CrewAI crews are standard Python scripts, so you can invoke them via cron, Airflow, Celery, or any task scheduler. The crew.kickoff() method runs synchronously by default, making it straightforward to integrate into existing pipelines.