How to integrate Miro MCP with CrewAI

This guide walks you through connecting Miro to CrewAI using the Composio tool router. By the end, you'll have a working Miro agent that can create a new board for marketing brainstorm, list all boards owned by your team, show members of the q2 planning board through natural language commands. This guide will help you understand how to give your CrewAI agent real control over a Miro account through Composio's Miro MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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Miro is a collaborative online whiteboard platform for teams to brainstorm, design, and manage projects visually. It streamlines teamwork by enabling real-time idea sharing, diagramming, and workflow planning in a single space.

73 Tools

Introduction

This guide walks you through connecting Miro to CrewAI using the Composio tool router. By the end, you'll have a working Miro agent that can create a new board for marketing brainstorm, list all boards owned by your team, show members of the q2 planning board through natural language commands.

This guide will help you understand how to give your CrewAI agent real control over a Miro account through Composio's Miro MCP server.

Before we dive in, let's take a quick look at the key ideas and tools involved.

Also integrate Miro with

ChatGPTOpenAI Agents SDKClaude Agent SDKClaude CodeClaude CoworkCodexOpenCodeCursorVS CodeOpenClawHermesCLIGoogle ADKLangChainVercel AI SDKMastra AILlamaIndex

TL;DR

Here's what you'll learn:
  • Get a Composio API key and configure your Miro connection
  • Set up CrewAI with an MCP enabled agent
  • Create a Tool Router session or standalone MCP server for Miro
  • Build a conversational loop where your agent can execute Miro operations

What is CrewAI?

CrewAI is a powerful framework for building multi-agent AI systems. It provides primitives for defining agents with specific roles, creating tasks, and orchestrating workflows through crews.

Key features include:

  • Agent Roles: Define specialized agents with specific goals and backstories
  • Task Management: Create tasks with clear descriptions and expected outputs
  • Crew Orchestration: Combine agents and tasks into collaborative workflows
  • MCP Integration: Connect to external tools through Model Context Protocol

What is the Miro MCP server, and what's possible with it?

The Miro MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Miro account. It provides structured and secure access to your whiteboards, so your agent can create new boards, manage board content, organize workflows, and collaborate visually—all on your behalf.

  • Automated board creation and setup: Instantly instruct your agent to create new Miro boards with specific names and descriptions for projects, brainstorming, or workshops.
  • Visual content management: Ask your agent to add, retrieve, or delete items such as shapes, sticky notes, app cards, or document items from any board, keeping your workspace tidy and up to date.
  • Efficient team and member management: Have your agent fetch and list all members of a board so you can easily track collaborators and manage access.
  • Seamless board organization and retrieval: Let your agent search and retrieve boards by team, owner, or keyword to keep your workspace organized and easy to navigate.
  • Connector and tag insights: Direct your agent to get details on connectors and tags used within boards, helping you map relationships and categorize content visually.

What is the Composio tool router, and how does it fit here?

What is Composio SDK?

Composio's Composio SDK helps agents find the right tools for a task at runtime. You can plug in multiple toolkits (like Gmail, HubSpot, and GitHub), and the agent will identify the relevant app and action to complete multi-step workflows. This can reduce token usage and improve the reliability of tool calls. Read more here: Getting started with Composio SDK

The tool router generates a secure MCP URL that your agents can access to perform actions.

How the Composio SDK works

The Composio SDK follows a three-phase workflow:

  1. Discovery: Searches for tools matching your task and returns relevant toolkits with their details.
  2. Authentication: Checks for active connections. If missing, creates an auth config and returns a connection URL via Auth Link.
  3. Execution: Executes the action using the authenticated connection.

Step-by-step Guide

Step by step08 STEPS
1

Prerequisites

Before starting, make sure you have:
  • Python 3.9 or higher
  • A Composio account and API key
  • A Miro connection authorized in Composio
  • An OpenAI API key for the CrewAI LLM
  • Basic familiarity with Python
2

Getting API Keys for OpenAI and Composio

OpenAI API Key
  • Go to the OpenAI dashboard and create an API key. You'll need credits to use the models, or you can connect to another model provider.
  • Keep the API key safe.
Composio API Key
  • Log in to the Composio dashboard.
  • Navigate to your API settings and generate a new API key.
  • Store this key securely as you'll need it for authentication.
3

Install dependencies

bash
pip install composio crewai crewai-tools[mcp] python-dotenv
What's happening:
  • composio connects your agent to Miro via MCP
  • crewai provides Agent, Task, Crew, and LLM primitives
  • crewai-tools[mcp] includes MCP helpers
  • python-dotenv loads environment variables from .env
4

Set up environment variables

bash
COMPOSIO_API_KEY=your_composio_api_key_here
USER_ID=your_user_id_here
OPENAI_API_KEY=your_openai_api_key_here

Create a .env file in your project root.

What's happening:

  • COMPOSIO_API_KEY authenticates with Composio
  • USER_ID scopes the session to your account
  • OPENAI_API_KEY lets CrewAI use your chosen OpenAI model
5

Import dependencies

python
import os
from composio import Composio
from crewai import Agent, Task, Crew
from crewai_tools import MCPServerAdapter
import dotenv

dotenv.load_dotenv()

COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY")
COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID")

if not COMPOSIO_API_KEY:
    raise ValueError("COMPOSIO_API_KEY is not set")
if not COMPOSIO_USER_ID:
    raise ValueError("COMPOSIO_USER_ID is not set")
What's happening:
  • CrewAI classes define agents and tasks, and run the workflow
  • MCPServerHTTP connects the agent to an MCP endpoint
  • Composio will give you a short lived Miro MCP URL
6

Create a Composio Tool Router session for Miro

python
composio_client = Composio(api_key=COMPOSIO_API_KEY)
session = composio_client.create(user_id=COMPOSIO_USER_ID, toolkits=["miro"])

url = session.mcp.url
What's happening:
  • You create a Miro only session through Composio
  • Composio returns an MCP HTTP URL that exposes Miro tools
7

Initialize the MCP Server

python
server_params = {
    "url": url,
    "transport": "streamable-http",
    "headers": {"x-api-key": COMPOSIO_API_KEY},
}

with MCPServerAdapter(server_params) as tools:
    agent = Agent(
        role="Search Assistant",
        goal="Help users search the internet effectively",
        backstory="You are a helpful assistant with access to search tools.",
        tools=tools,
        verbose=False,
        max_iter=10,
    )
What's Happening:
  • Server Configuration: The code sets up connection parameters including the MCP server URL, streamable HTTP transport, and Composio API key authentication.
  • MCP Adapter Bridge: MCPServerAdapter acts as a context manager that converts Composio MCP tools into a CrewAI-compatible format.
  • Agent Setup: Creates a CrewAI Agent with a defined role (Search Assistant), goal (help with internet searches), and access to the MCP tools.
  • Configuration Options: The agent includes settings like verbose=False for clean output and max_iter=10 to prevent infinite loops.
  • Dynamic Tool Usage: Once created, the agent automatically accesses all Composio Search tools and decides when to use them based on user queries.
8

Create a CLI Chatloop and define the Crew

python
print("Chat started! Type 'exit' or 'quit' to end.\n")

conversation_context = ""

while True:
    user_input = input("You: ").strip()

    if user_input.lower() in ["exit", "quit", "bye"]:
        print("\nGoodbye!")
        break

    if not user_input:
        continue

    conversation_context += f"\nUser: {user_input}\n"
    print("\nAgent is thinking...\n")

    task = Task(
        description=(
            f"Conversation history:\n{conversation_context}\n\n"
            f"Current request: {user_input}"
        ),
        expected_output="A helpful response addressing the user's request",
        agent=agent,
    )

    crew = Crew(agents=[agent], tasks=[task], verbose=False)
    result = crew.kickoff()
    response = str(result)

    conversation_context += f"Agent: {response}\n"
    print(f"Agent: {response}\n")
What's Happening:
  • Interactive CLI Setup: The code creates an infinite loop that continuously prompts for user input and maintains the entire conversation history in a string variable.
  • Input Validation: Empty inputs are ignored to prevent processing blank messages and keep the conversation clean.
  • Context Building: Each user message is appended to the conversation context, which preserves the full dialogue history for better agent responses.
  • Dynamic Task Creation: For every user input, a new Task is created that includes both the full conversation history and the current request as context.
  • Crew Execution: A Crew is instantiated with the agent and task, then kicked off to process the request and generate a response.
  • Response Management: The agent's response is converted to a string, added to the conversation context, and displayed to the user, maintaining conversational continuity.

Complete Code

Here's the complete code to get you started with Miro and CrewAI:

python
from crewai import Agent, Task, Crew, LLM
from crewai_tools import MCPServerAdapter
from composio import Composio
from dotenv import load_dotenv
import os

load_dotenv()

GOOGLE_API_KEY = os.getenv("GOOGLE_API_KEY")
COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY")
COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID")

if not GOOGLE_API_KEY:
    raise ValueError("GOOGLE_API_KEY is not set in the environment.")
if not COMPOSIO_API_KEY:
    raise ValueError("COMPOSIO_API_KEY is not set in the environment.")
if not COMPOSIO_USER_ID:
    raise ValueError("COMPOSIO_USER_ID is not set in the environment.")

# Initialize Composio and create a session
composio = Composio(api_key=COMPOSIO_API_KEY)
session = composio.create(
    user_id=COMPOSIO_USER_ID,
    toolkits=["miro"],
)
url = session.mcp.url

# Configure LLM
llm = LLM(
    model="gpt-5",
    api_key=os.getenv("OPENAI_API_KEY"),
)

server_params = {
    "url": url,
    "transport": "streamable-http",
    "headers": {"x-api-key": COMPOSIO_API_KEY},
}

with MCPServerAdapter(server_params) as tools:
    agent = Agent(
        role="Search Assistant",
        goal="Help users with internet searches",
        backstory="You are an expert assistant with access to Composio Search tools.",
        tools=tools,
        llm=llm,
        verbose=False,
        max_iter=10,
    )

    print("Chat started! Type 'exit' or 'quit' to end.\n")

    conversation_context = ""

    while True:
        user_input = input("You: ").strip()

        if user_input.lower() in ["exit", "quit", "bye"]:
            print("\nGoodbye!")
            break

        if not user_input:
            continue

        conversation_context += f"\nUser: {user_input}\n"
        print("\nAgent is thinking...\n")

        task = Task(
            description=(
                f"Conversation history:\n{conversation_context}\n\n"
                f"Current request: {user_input}"
            ),
            expected_output="A helpful response addressing the user's request",
            agent=agent,
        )

        crew = Crew(agents=[agent], tasks=[task], verbose=False)
        result = crew.kickoff()
        response = str(result)

        conversation_context += f"Agent: {response}\n"
        print(f"Agent: {response}\n")

Conclusion

You now have a CrewAI agent connected to Miro through Composio's Tool Router. The agent can perform Miro operations through natural language commands.

Next steps:

  • Add role-specific instructions to customize agent behavior
  • Plug in more toolkits for multi-app workflows
  • Chain tasks for complex multi-step operations
TOOLS

Supported Tools

Every Miro action and event your agent gets out of the box.

Attach Tag To Item

Tool to attach an existing tag to a specific item on a Miro board.

Create App Card Item

Tool to add an app card item to a board.

Create Board

Tool to create a new board.

Create Card Item

Tool to create a card item on a Miro board.

Create Connector

Tool to create a connector (edge/arrow) that links two existing board items.

Create Document Item

Tool to create a document item on a Miro board by providing a URL to the document.

Create Document Item Using File From Device

Tool to create a document item on a Miro board using a URL to the document.

Create Embed Item

Tool to create an embed item on a Miro board by providing a URL to embed content (YouTube videos, websites, etc.

Create Frame Item

Tool to add a frame item to a Miro board.

Create Group

Tool to create a group on a Miro board by grouping multiple items together.

Create Image Item Using Local File

Tool to create an image item on a Miro board by uploading a local image file.

Create Items in Bulk

Tool to create multiple items on a Miro board in a single request.

Create Mind Map Node (Experimental)

Tool to create a mind map node on a Miro board.

Create Shape Item

Tool to create a shape item on a Miro board.

Create Sticky Note Item

Tool to create a sticky note item on a Miro board.

Create Tag

Tool to create a new tag on a Miro board.

Create Text Item

Tool to create a text item on a Miro board.

Delete App Card Item

Tool to delete an app card item from a board.

Delete Card Item

Tool to delete a card item from a board.

Delete Connector

Tool to delete a specific connector from a board.

Delete Document Item

Tool to delete a document item from a board.

Delete Embed Item

Tool to delete an embed item from a board.

Delete Frame Item

Tool to delete a frame item from a Miro board.

Delete Group

Tool to delete a group from a board.

Delete Image Item

Tool to delete an image item from a board.

Delete Item

Tool to delete a specific item from a board.

Delete Mind Map Node (Experimental)

Tool to delete a mind map node from a board.

Delete Shape Item

Tool to delete a shape item from a board.

Delete Sticky Note Item

Tool to delete a sticky note item from a board.

Delete Tag

Tool to delete a specific tag from a board.

Delete Text Item

Tool to delete a text item from a board.

Get All Groups

Tool to retrieve all groups on a Miro board with cursor-based pagination.

Get App Card Item 2

Tool to retrieve a specific app card item by its ID from a Miro board.

Get Board Items

Tool to list items on a Miro board (shapes, stickies, cards, etc.

Get Board Members

Tool to retrieve a list of members for a board.

Get Boards V2

Tool to retrieve accessible boards with optional filters.

Get Card Item

Tool to retrieve a specific card item from a Miro board.

Get Connector

Tool to retrieve a specific connector by its ID.

Get Connectors

Tool to retrieve a list of connectors on a board.

Get Document Item

Tool to retrieve a specific document item from a Miro board by its ID.

Get Embed Item

Tool to retrieve a specific embed item from a board by its ID.

Get Frame Item

Tool to retrieve a specific frame item from a Miro board.

Get Group By ID

Tool to retrieve a specific group by its ID.

Get Image Item

Tool to retrieve a specific image item from a board.

Get Item Tags

Tool to retrieve tags attached to a specific item on a Miro board.

Get Mind Map Node

Tool to retrieve a specific mind map node from a board.

Get Mind Map Nodes (Experimental)

Tool to retrieve mind map nodes from a Miro board.

Get oEmbed Data

Tool to retrieve oEmbed data for a Miro board.

Get Shape Item

Tool to retrieve a specific shape item from a Miro board by its ID.

Get Specific Board

Tool to retrieve detailed information about a specific board by its ID.

Get Specific Board Member

Tool to retrieve details of a specific board member.

Get Specific Item

Tool to retrieve a specific item from a Miro board by its ID.

Get Sticky Note Item

Tool to retrieve a specific sticky note item from a board by its ID.

Get Tag

Tool to retrieve details of a specific tag on a board.

Get Text Item

Tool to retrieve a specific text item from a Miro board by its ID.

List Board Tags

Tool to list all tags on a Miro board.

Get Organization Context

Retrieves the organization associated with the current access token.

Share Board

Tool to share a board by inviting users via email.

Update App Card Item 2

Tool to update an app card item on a Miro board.

Update Board

Tool to update properties of a specific board.

Update Board Member

Tool to update the role of a specific board member.

Update Card Item

Tool to update a card item on a Miro board.

Update Connector

Tool to update an existing connector on a Miro board.

Update Document Item

Tool to update a document item on a Miro board.

Update Embed Item

Tool to update an embed item on a board.

Update Frame Item

Tool to update a frame item on a Miro board.

Update Group

Tool to update a group on a Miro board with new items.

Update Image Item

Tool to update an existing image item on a board.

Update Item Position or Parent

Tool to update an item's position or parent frame on a Miro board.

Update Shape Item

Tool to update an existing shape item on a Miro board.

Update Sticky Note Item

Tool to update a sticky note item on a Miro board.

Update Tag

Tool to update a tag on a board.

Update Text Item

Tool to update a text item on a Miro board.

FRAMEWORKS

How to build Miro MCP Agent with another framework

ChatGPT logo

ChatGPT

Use Miro MCP with ChatGPT

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Miro MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Miro MCP with Claude Agent SDK

Claude Code logo

Claude Code

Use Miro MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Miro MCP with Claude Cowork

Codex logo

Codex

Use Miro MCP with Codex

Cursor logo

Cursor

Use Miro MCP with Cursor

OpenClaw logo

OpenClaw

Use Miro MCP with OpenClaw

Hermes logo

Hermes

Use Miro MCP with Hermes

CLI logo

CLI

Use Miro MCP with CLI

Google ADK logo

Google ADK

Use Miro MCP with Google ADK

LangChain logo

LangChain

Use Miro MCP with LangChain

Vercel AI SDK logo

Vercel AI SDK

Use Miro MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Miro MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Miro MCP with LlamaIndex

OpenCode logo

OpenCode

Use Miro MCP with OpenCode

VS Code logo

VS Code

Use Miro MCP with VS Code

FAQ

Frequently asked questions

With a standalone Miro MCP server, the agents and LLMs can only access a fixed set of Miro tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Miro and many other apps based on the task at hand, all through a single MCP endpoint.

Yes, you can. CrewAI fully supports MCP integration. You get structured tool calling, message history handling, and model orchestration while Tool Router takes care of discovering and serving the right Miro tools.

Yes, absolutely. You can configure which Miro scopes and actions are allowed when connecting your account to Composio. You can also bring your own OAuth credentials or API configuration so you keep full control over what the agent can do.

All sensitive data such as tokens, keys, and configuration is fully encrypted at rest and in transit. Composio is SOC 2 Type 2 compliant and follows strict security practices so your Miro data and credentials are handled as safely as possible.

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Karan skipped his own birthday party to fix our critical issue. It was 10pm and he diverted his Waymo to help us instead. This really sets the bar — it shows the commitment you need when users rely on your software.

Harsha Gaddipati
Harsha Gaddipati
Co-founder, Slashy

A lot of students tell us that the moment their connected tools start talking to each other inside Opennote feels almost magical. The agent just knows them, and it's immensely helped keep new users on the platform.

Abhi Arya
Abhi Arya
Co-founder, Opennote

We chose Composio over Pipedream because it delivered depth where it mattered — niche tools and tricky edge cases other platforms simply ignored. That gave us confidence to scale without compromising.

Nirman Dave
Nirman Dave
CEO, Zams

As a solo builder, shipping fast is life or death. The only way I can outcompete incumbents is by outmanoeuvring them. Getting bogged down managing agent auth would have been a death sentence.

Ryan Yu
Ryan Yu
Founder, Extra Thursday

Before Composio, adding tool integrations was slow and resource-intensive. Each one could take weeks of engineering time, and maintaining them meant constantly keeping up with API changes.

Tomisin Jenrola
Tomisin Jenrola
Founder & CEO, SwarmZero

With hands-on help from their founder, we integrated Gmail and Google Drive in just 30 minutes. This level of personal support and commitment is exactly what startups should strive for.

Jerome Leclanche
Jerome Leclanche
Co-Founder, Ingram Technologies