How to integrate Penpot MCP with LangChain

This guide walks you through connecting Penpot to LangChain 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 LangChain 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 LangChain 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 LangChain 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 ADKVercel AI SDKMastra AILlamaIndexCrewAI

TL;DR

Here's what you'll learn:
  • Get and set up your OpenAI and Composio API keys
  • Connect your Penpot project to Composio
  • Create a Tool Router MCP session for Penpot
  • Initialize an MCP client and retrieve Penpot tools
  • Build a LangChain agent that can interact with Penpot
  • Set up an interactive chat interface for testing

What is LangChain?

LangChain is a framework for developing applications powered by language models. It provides tools and abstractions for building agents that can reason, use tools, and maintain conversation context.

Key features include:

  • Agent Framework: Build agents that can use tools and make decisions
  • MCP Integration: Connect to external services through Model Context Protocol adapters
  • Memory Management: Maintain conversation history across interactions
  • Multi-Provider Support: Works with OpenAI, Anthropic, and other LLM providers

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 step10 STEPS
1

Prerequisites

Before starting this tutorial, make sure you have:
  • Python 3.10 or higher installed on your system
  • A Composio account with an API key
  • An OpenAI API key
  • Basic familiarity with Python and async programming
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

npm install @composio/langchain @langchain/core @langchain/openai @langchain/mcp-adapters dotenv

Install the required packages for LangChain with MCP support.

What's happening:

  • @composio/langchain provides Composio integration for LangChain
  • @langchain/mcp-adapters enables MCP client connections
  • @langchain/core is the core agent framework
  • dotenv/config loads environment variables
4

Set up environment variables

bash
COMPOSIO_API_KEY=your_composio_api_key_here
COMPOSIO_USER_ID=your_composio_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 your requests to Composio's API
  • COMPOSIO_USER_ID identifies the user for session management
  • OPENAI_API_KEY enables access to OpenAI's language models
5

Import dependencies

import { Composio } from '@composio/core';
import { LangchainProvider } from '@composio/langchain';
import { MultiServerMCPClient } from "@langchain/mcp-adapters";
import { createAgent } from "langchain";
import * as readline from 'readline';
import 'dotenv/config';

dotenv.config();
What's happening:
  • We're importing LangChain's MCP adapter and Composio SDK
  • The dotenv/config import loads environment variables from your .env file
  • This setup prepares the foundation for connecting LangChain with Penpot functionality through MCP
6

Initialize Composio client

const composioApiKey = process.env.COMPOSIO_API_KEY;
const userId = process.env.COMPOSIO_USER_ID;

if (!composioApiKey) throw new Error('COMPOSIO_API_KEY is not set');
if (!userId) throw new Error('COMPOSIO_USER_ID is not set');

async function main() {
    const composio = new Composio({
        apiKey: composioApiKey as string,
        provider: new LangchainProvider()
    });
What's happening:
  • We're loading the COMPOSIO_API_KEY from environment variables and validating it exists
  • Creating a Composio instance that will manage our connection to Penpot tools
  • Validating that COMPOSIO_USER_ID is also set before proceeding
7

Create a Tool Router session

const session = await composio.create(
    userId as string,
    {
        toolkits: ['penpot']
    }
);

const url = session.mcp.url;
What's happening:
  • We're creating a Tool Router session that gives your agent access to Penpot tools
  • The create method takes the user ID and specifies which toolkits should be available
  • The returned session.mcp.url is the MCP server URL that your agent will use
  • This approach allows the agent to dynamically load and use Penpot tools as needed
8

Configure the agent with the MCP URL

const client = new MultiServerMCPClient({
    "penpot-agent": {
        transport: "http",
        url: url,
        headers: {
            "x-api-key": process.env.COMPOSIO_API_KEY
        }
    }
});

const tools = await client.getTools();

const agent = createAgent({ model: "gpt-5", tools });
What's happening:
  • We're creating a MultiServerMCPClient that connects to our Penpot MCP server via HTTP
  • The client is configured with a name and the URL from our Tool Router session
  • getTools() retrieves all available Penpot tools that the agent can use
  • We're creating a LangChain agent using the GPT-5 model
9

Set up interactive chat interface

let conversationHistory: any[] = [];

console.log("Chat started! Type 'exit' or 'quit' to end the conversation.\n");
console.log("Ask any Penpot related question or task to the agent.\n");

const rl = readline.createInterface({
    input: process.stdin,
    output: process.stdout,
    prompt: 'You: '
});

rl.prompt();

rl.on('line', async (userInput: string) => {
    const trimmedInput = userInput.trim();

    if (['exit', 'quit', 'bye'].includes(trimmedInput.toLowerCase())) {
        console.log("\nGoodbye!");
        rl.close();
        process.exit(0);
    }

    if (!trimmedInput) {
        rl.prompt();
        return;
    }

    conversationHistory.push({ role: "user", content: trimmedInput });
    console.log("\nAgent is thinking...\n");

    const response = await agent.invoke({ messages: conversationHistory });
    conversationHistory = response.messages;

    const finalResponse = response.messages[response.messages.length - 1]?.content;
    console.log(`Agent: ${finalResponse}\n`);
        
        rl.prompt();
    });

    rl.on('close', () => {
        console.log('\n👋 Session ended.');
        process.exit(0);
    });
What's happening:
  • We initialize an empty conversationHistory list to maintain context across interactions
  • A readline interface is used to continuously accept user input from the command line
  • When a user types a message, it's added to the conversation history and sent to the agent
  • The agent processes the request using the invoke() method with the full conversation history
  • Users can type 'exit', 'quit', or 'bye' to end the chat session gracefully
10

Run the application

main().catch((err) => {
    console.error('Fatal error:', err);
    process.exit(1);
});
What's happening:
  • We call the main() function to start the application

Complete Code

Here's the complete code to get you started with Penpot and LangChain:

import { Composio } from '@composio/core';
import { LangchainProvider } from '@composio/langchain';
import { MultiServerMCPClient } from "@langchain/mcp-adapters";  
import { createAgent } from "langchain";
import * as readline from 'readline';
import 'dotenv/config';

const composioApiKey = process.env.COMPOSIO_API_KEY;
const userId = process.env.COMPOSIO_USER_ID;

if (!composioApiKey) throw new Error('COMPOSIO_API_KEY is not set');
if (!userId) throw new Error('COMPOSIO_USER_ID is not set');

async function main() {
    const composio = new Composio({
        apiKey: composioApiKey as string,
        provider: new LangchainProvider()
    });

    const session = await composio.create(
        userId as string,
        {
            toolkits: ['penpot']
        }
    );

    const url = session.mcp.url;
    
    const client = new MultiServerMCPClient({
        "penpot-agent": {
            transport: "http",
            url: url,
            headers: {
                "x-api-key": process.env.COMPOSIO_API_KEY
            }
        }
    });
    
    const tools = await client.getTools();
  
    const agent = createAgent({ model: "gpt-5", tools });
    
    let conversationHistory: any[] = [];
    
    console.log("Chat started! Type 'exit' or 'quit' to end the conversation.\n");
    console.log("Ask any Penpot related question or task to the agent.\n");
    
    const rl = readline.createInterface({
        input: process.stdin,
        output: process.stdout,
        prompt: 'You: '
    });

    rl.prompt();

    rl.on('line', async (userInput: string) => {
        const trimmedInput = userInput.trim();
        
        if (['exit', 'quit', 'bye'].includes(trimmedInput.toLowerCase())) {
            console.log("\nGoodbye!");
            rl.close();
            process.exit(0);
        }
        
        if (!trimmedInput) {
            rl.prompt();
            return;
        }
        
        conversationHistory.push({ role: "user", content: trimmedInput });
        console.log("\nAgent is thinking...\n");
        
        const response = await agent.invoke({ messages: conversationHistory });
        conversationHistory = response.messages;
        
        const finalResponse = response.messages[response.messages.length - 1]?.content;
        console.log(`Agent: ${finalResponse}\n`);
        
        rl.prompt();
    });

    rl.on('close', () => {
        console.log('\nSession ended.');
        process.exit(0);
    });
}

main().catch((err) => {
    console.error('Fatal error:', err);
    process.exit(1);
});

Conclusion

You've successfully built a LangChain agent that can interact with Penpot through Composio's Tool Router.

Key features of this implementation:

  • Dynamic tool loading through Composio's Tool Router
  • Conversation history maintenance for context-aware responses
  • Async Python provides clean, efficient execution of agent workflows
You can extend this further by adding error handling, implementing specific business logic, or integrating additional Composio toolkits to create multi-app workflows.
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

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

CrewAI logo

CrewAI

Use Penpot MCP with CrewAI

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. LangChain 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