How to integrate Penpot MCP with CrewAI

This guide walks you through connecting Penpot to CrewAI using the Composio tool router. By the end, you'll have a working Penpot agent that can review comments on penpot design files, create prototype links for mobile screens, list recent changes in team projects through natural language commands. This guide will help you understand how to give your CrewAI agent real control over a Penpot account through Composio's Penpot MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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Penpot is an open-source design and prototyping platform for product teams. It helps teams collaborate on UI design with web-based, developer-friendly workflows.

90 Tools

Introduction

This guide walks you through connecting Penpot to CrewAI using the Composio tool router. By the end, you'll have a working Penpot agent that can review comments on penpot design files, create prototype links for mobile screens, list recent changes in team projects through natural language commands.

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

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

Also integrate Penpot with

OpenAI Agents SDKClaude Agent SDKClaude CodeClaude CoworkCodexOpenClawHermesCLIGoogle ADKLangChainVercel AI SDKMastra AILlamaIndex

TL;DR

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

The Penpot MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Penpot account. It provides structured and secure access to your teams, projects, design files, comments, and webhooks, so your agent can organize projects, manage files, coordinate feedback, find design work, and review team membership on your behalf.

  • Team and project organization: Have your agent create teams and projects, list your existing workspaces, and retrieve project or team details.
  • Design file management: Let the agent create and update design files, inspect file information, and list every file within a project.
  • Design search and discovery: Direct your agent to search for Penpot files by name or content across a team.
  • Collaborative design feedback: Instruct your agent to create comment threads at specific places in a design and retrieve existing discussions for review.
  • Team updates and notifications: Have your agent list team members and create webhooks that notify your systems about team events.

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 Penpot 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 Penpot 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 Penpot MCP URL
6

Create a Composio Tool Router session for Penpot

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

url = session.mcp.url
What's happening:
  • You create a Penpot only session through Composio
  • Composio returns an MCP HTTP URL that exposes Penpot 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 Penpot 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=["penpot"],
)
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 Penpot through Composio's Tool Router. The agent can perform Penpot 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 Penpot action and event your agent gets out of the box.

Create Access Token

Tool to create a personal access token for API authentication in Penpot.

Create Comment Thread

Tool to create a new comment thread on a Penpot file at a specific position.

Create File

Tool to create a new design file in a Penpot project.

Create Project

Tool to create a new project within a team in Penpot.

Create Team

Tool to create a new team in Penpot.

Create Team Access Request

Tool to request an invitation to join a Penpot team.

Create Webhook

Create a webhook for a team to receive event notifications.

Delete Access Token

Tool to delete a personal access token from Penpot.

Delete Comment

Tool to delete a comment from a Penpot design file.

Delete File Snapshot

Tool to delete a file snapshot in Penpot.

Delete Project

Tool to delete a project from Penpot.

Delete Team

Tool to delete a team from Penpot.

Permanently Delete Team Files

Tool to permanently delete specified files from a Penpot team.

Delete Team Invitation

Tool to delete a pending team invitation in Penpot.

Delete Team Member

Tool to remove a member from a team in Penpot.

Delete Webhook

Tool to delete a webhook by its UUID.

Duplicate File

Tool to duplicate a single file within the same team in Penpot.

Duplicate Project

Tool to duplicate an entire Penpot project with all its files.

Get Access Tokens

Tool to list all personal access tokens for the authenticated user.

Get All Projects

Tool to retrieve all projects across all teams in Penpot.

Get Builtin Templates

Tool to get the list of builtin templates available in Penpot.

Get Comments

Tool to retrieve all comments in a comment thread.

Get Comment Thread

Tool to retrieve a specific comment thread from a Penpot file.

Get Comment Threads

Tool to retrieve all comment threads for a Penpot file.

Get File

Tool to retrieve a Penpot file by its ID.

Get File Info

Tool to retrieve basic information about a Penpot file by its ID.

Get File Libraries

Tool to retrieve libraries linked to a Penpot file.

Get File Object Thumbnails

Tool to retrieve thumbnails for objects in a Penpot file.

Get File Snapshots

Retrieves all snapshots for a specific Penpot file.

Get File Summary

Tool to retrieve a summary of file contents and statistics from Penpot.

Get Font Variants

Tool to retrieve font variants for a team, file, project, or share in Penpot.

Get Library File References

Tool to get files that reference a shared library.

Get Library Usage

Tool to get usage statistics for a library.

Get Owned Teams

Tool to list teams owned by the current user.

Get Page

Tool to retrieve page data from a Penpot file.

Get Profiles for File Comments

Tool to retrieve profiles of users who have commented on a Penpot file.

Get Project

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

Get Project Files

Tool to retrieve all files in a Penpot project.

Get SSO Provider

Tool to retrieve SSO provider information for an email address.

Get Subscription Usage

Tool to get subscription usage information for the current user.

Get Team

Tool to retrieve team details by ID.

Get Team Deleted Files

Tool to retrieve deleted files from a team's trash in Penpot.

Get Team Info

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

Get Team Invitations

Tool to list pending invitations for a team in Penpot.

Get Team Members

Tool to list all members of a team in Penpot.

Get Teams

Tool to list all teams the authenticated user is a member of.

Get Team Shared Files

Tool to retrieve shared library files for a Penpot team.

Get Team Stats

Tool to retrieve statistics for a specific Penpot team by its ID.

Get Team Users

Tool to retrieve users in a team by team ID or file ID.

Get Unread Comment Threads

Tool to retrieve comment threads with unread comments for a specific team.

Get View Only Bundle

Tool to retrieve data bundle for view-only file access in Penpot.

Get Webhooks

Tool to retrieve all webhooks configured for a team.

Has File Libraries

Tool to check if a Penpot file has linked libraries.

Ignore File Library Sync Status

Tool to ignore library sync status updates for a file.

Link File to Library

Tool to link a file to a library in Penpot.

Lock File Snapshot

Tool to lock a file snapshot in Penpot to prevent deletion.

Logout

Tool to clear the authentication cookie and logout the current session.

Mark All Threads As Read

Tool to mark all comment threads as read in Penpot.

Move Files

Tool to move files from one project to another in Penpot.

Move Project

Tool to move a project to a different team in Penpot.

Prepare Register Profile

Tool to prepare user registration by validating email and sending verification in Penpot.

Push Audit Events

Tool to push audit events to Penpot for tracking system behavior and user actions.

Register Profile

Tool to complete user registration with profile details using a verification token.

Rename File

Tool to rename a design file in Penpot.

Rename Project

Tool to rename an existing project in Penpot.

Request Profile Recovery

Tool to request a password/profile recovery email.

Restore Deleted Team Files

Tool to restore deleted files in a Penpot team.

Restore File Snapshot

Tool to restore a Penpot file to a previous snapshot.

Search Files

Tool to search for files by name or content in a Penpot team.

Send User Feedback

Tool to send user feedback to Penpot.

Set File Shared

Tool to set file sharing status in Penpot (enable/disable shared library).

Unlink File from Library

Tool to unlink a file from a shared library in Penpot.

Unlock File Snapshot

Tool to unlock a locked file snapshot in Penpot.

Update Comment

Tool to update the content of an existing comment in a Penpot design file.

Update Comment Thread

Tool to update the resolution status of a comment thread in Penpot.

Update Comment Thread Frame

Tool to update the frame associated with a comment thread in Penpot.

Update Comment Thread Position

Tool to update the position of a comment thread in Penpot.

Update Comment Thread Status

Tool to update the status of a comment thread in Penpot (e.

Update File

Tool to update a Penpot file with changes.

Update File Library Sync Status

Tool to update the synchronization status of a file->library link.

Update File Snapshot

Tool to update a file snapshot metadata in Penpot.

Update Font

Tool to update a font's metadata in Penpot.

Update Profile

Tool to update the current authenticated user's profile information.

Update Profile Notifications

Tool to update notification settings for the authenticated user's profile.

Update Profile Props

Tool to update custom properties for the authenticated user's profile.

Update Project Pin

Tool to update the pin status of a project in Penpot.

Update Team

Tool to update team settings in Penpot.

Update Team Invitation Role

Tool to update the role of a pending team invitation in Penpot.

Update Webhook

Tool to update an existing webhook configuration.

Verify Token

Tool to verify an authentication or registration token in Penpot.

FRAMEWORKS

How to build Penpot MCP Agent with another framework

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Penpot MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Penpot MCP with Claude Agent SDK

Claude Code logo

Claude Code

Use Penpot MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Penpot MCP with Claude Cowork

Codex logo

Codex

Use Penpot MCP with Codex

OpenClaw logo

OpenClaw

Use Penpot MCP with OpenClaw

Hermes logo

Hermes

Use Penpot MCP with Hermes

CLI logo

CLI

Use Penpot MCP with CLI

Google ADK logo

Google ADK

Use Penpot MCP with Google ADK

LangChain logo

LangChain

Use Penpot MCP with LangChain

Vercel AI SDK logo

Vercel AI SDK

Use Penpot MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Penpot MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Penpot MCP with LlamaIndex

FAQ

Frequently asked questions

With a standalone Penpot MCP server, the agents and LLMs can only access a fixed set of Penpot tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Penpot 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 Penpot tools.

Yes, absolutely. You can configure which Penpot 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 Penpot 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