How to integrate Figma MCP with OpenAI Agents SDK

This guide walks you through connecting Figma to the OpenAI Agents SDK using the Composio tool router. By the end, you'll have a working Figma agent that can add a comment to this figma file, convert design tokens to tailwind css, delete a reaction from a comment through natural language commands. This guide will help you understand how to give your OpenAI Agents SDK agent real control over a Figma account through Composio's Figma MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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Figma is a collaborative interface design tool for teams and individuals. It streamlines design workflows with real-time collaboration and easy sharing.

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Introduction

This guide walks you through connecting Figma to the OpenAI Agents SDK using the Composio tool router. By the end, you'll have a working Figma agent that can add a comment to this figma file, convert design tokens to tailwind css, delete a reaction from a comment through natural language commands.

This guide will help you understand how to give your OpenAI Agents SDK agent real control over a Figma account through Composio's Figma MCP server.

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

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TL;DR

Here's what you'll learn:
  • Get and set up your OpenAI and Composio API keys
  • Install the necessary dependencies
  • Initialize Composio and create a Tool Router session for Figma
  • Configure an AI agent that can use Figma as a tool
  • Run a live chat session where you can ask the agent to perform Figma operations

What is OpenAI Agents SDK?

The OpenAI Agents SDK is a lightweight framework for building AI agents that can use tools and maintain conversation state. It provides a simple interface for creating agents with hosted MCP tool support.

Key features include:

  • Hosted MCP Tools: Connect to external services through hosted MCP endpoints
  • SQLite Sessions: Persist conversation history across interactions
  • Simple API: Clean interface with Agent, Runner, and tool configuration
  • Streaming Support: Real-time response streaming for interactive applications

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

The Figma MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Figma account. It provides structured and secure access to your Figma workspace, so your agent can perform actions like commenting on designs, managing design tokens, linking developer resources, and automating collaboration workflows on your behalf.

  • Automated commenting and feedback loops: Have your agent add, reply to, or delete comments on Figma files and branches to streamline design reviews and team discussions.
  • Design token management and conversion: Let the agent extract, update, or convert design tokens in your files, including generating Tailwind CSS configurations for seamless dev handoff.
  • Developer resource integration: Automatically attach, update, or remove dev resources linked to Figma nodes, bridging the gap between design and development with contextual documentation or code references.
  • Webhook setup and automation: Enable your agent to create or delete webhooks for team events, making it easy to trigger notifications or workflows based on design activity.
  • Collaborative variable management: Empower the agent to batch-create, modify, or delete variables, collections, and modes across your design system, keeping everything consistent and up to date.

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 step09 STEPS
1

Prerequisites

Before starting, make sure you have:
  • Composio API Key and OpenAI API Key
  • Primary know-how of OpenAI Agents SDK
  • A live Figma project
  • Some knowledge of Python or Typescript
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
3

Install dependencies

npm install @composio/openai-agents @openai/agents dotenv

Install the Composio SDK and the OpenAI Agents SDK.

4

Set up environment variables

bash
OPENAI_API_KEY=sk-...your-api-key
COMPOSIO_API_KEY=your-api-key
USER_ID=composio_user@gmail.com

Create a .env file and add your OpenAI and Composio API keys.

5

Import dependencies

import 'dotenv/config';
import { Composio } from '@composio/core';
import { OpenAIAgentsProvider } from '@composio/openai-agents';
import { Agent, hostedMcpTool, run, OpenAIConversationsSession } from '@openai/agents';
import * as readline from 'readline';
What's happening:
  • You're importing all necessary libraries.
  • The Composio and OpenAIAgentsProvider classes are imported to connect your OpenAI agent to Composio tools like Figma.
6

Set up the Composio instance

dotenv.config();

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

if (!composioApiKey) {
  throw new Error('COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key');
}
if (!userId) {
  throw new Error('USER_ID is not set');
}

// Initialize Composio
const composio = new Composio({
  apiKey: composioApiKey,
  provider: new OpenAIAgentsProvider(),
});
What's happening:
  • dotenv.config() loads your .env file so COMPOSIO_API_KEY and USER_ID are available as environment variables.
  • Creating a Composio instance using the API Key and OpenAIAgentsProvider class.
7

Create a Tool Router session

// Create Tool Router session for Figma
const session = await composio.create(userId as string, {
  toolkits: ['figma'],
});
const mcpUrl = session.mcp.url;

What is happening:

  • You give the Tool Router the user id and the toolkits you want available. Here, it is only figma.
  • The router checks the user's Figma connection and prepares the MCP endpoint.
  • The returned session.mcp.url is the MCP URL that your agent will use to access Figma.
  • This approach keeps things lightweight and lets the agent request Figma tools only when needed during the conversation.
8

Configure the agent

// Configure agent with MCP tool
const agent = new Agent({
  name: 'Assistant',
  model: 'gpt-5',
  instructions:
    'You are a helpful assistant that can access Figma. Help users perform Figma operations through natural language.',
  tools: [
    hostedMcpTool({
      serverLabel: 'tool_router',
      serverUrl: mcpUrl,
      headers: { 'x-api-key': composioApiKey },
      requireApproval: 'never',
    }),
  ],
});
What's happening:
  • We're creating an Agent instance with a name, model (gpt-5), and clear instructions about its purpose.
  • The agent's instructions tell it that it can access Figma and help with queries, inserts, updates, authentication, and fetching database information.
  • The tools array includes a hostedMcpTool that connects to the MCP server URL we created earlier.
  • The headers object includes the Composio API key for secure authentication with the MCP server.
  • requireApproval: 'never' means the agent can execute Figma operations without asking for permission each time, making interactions smoother.
9

Start chat loop and handle conversation

// Keep conversation state across turns
const conversationSession = new OpenAIConversationsSession();

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

console.log('\nComposio Tool Router session created.');
console.log('\nChat started. Type your requests below.');
console.log("Commands: 'exit', 'quit', or 'q' to end\n");

try {
  const first = await run(agent, 'What can you help me with?', { session: conversationSession });
  console.log(`Assistant: ${first.finalOutput}\n`);
} catch (e) {
  console.error('Error:', e instanceof Error ? e.message : e, '\n');
}

rl.prompt();

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

  if (['exit', 'quit', 'q'].includes(text.toLowerCase())) {
    console.log('Goodbye!');
    rl.close();
    process.exit(0);
  }

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

  try {
    const result = await run(agent, text, { session: conversationSession });
    console.log(`\nAssistant: ${result.finalOutput}\n`);
  } catch (e) {
    console.error('Error:', e instanceof Error ? e.message : e, '\n');
  }

  rl.prompt();
});

rl.on('close', () => {
  console.log('\n👋 Session ended.');
  process.exit(0);
});
What's happening:
  • The program prints a session URL that you visit to authorize Figma.
  • After authorization, the chat begins.
  • Each message you type is processed by the agent using run().
  • The responses are printed to the console.
  • Typing exit, quit, or q cleanly ends the chat.

Complete Code

Here's the complete code to get you started with Figma and OpenAI Agents SDK:

import 'dotenv/config';
import { Composio } from '@composio/core';
import { OpenAIAgentsProvider } from '@composio/openai-agents';
import { Agent, hostedMcpTool, run, OpenAIConversationsSession } from '@openai/agents';
import * as readline from 'readline';

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

if (!composioApiKey) {
  throw new Error('COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key');
}
if (!userId) {
  throw new Error('USER_ID is not set');
}

// Initialize Composio
const composio = new Composio({
  apiKey: composioApiKey,
  provider: new OpenAIAgentsProvider(),
});

async function main() {
  // Create Tool Router session
  const session = await composio.create(userId as string, {
    toolkits: ['figma'],
  });
  const mcpUrl = session.mcp.url;

  // Configure agent with MCP tool
  const agent = new Agent({
    name: 'Assistant',
    model: 'gpt-5',
    instructions:
      'You are a helpful assistant that can access Figma. Help users perform Figma operations through natural language.',
    tools: [
      hostedMcpTool({
        serverLabel: 'tool_router',
        serverUrl: mcpUrl,
        headers: { 'x-api-key': composioApiKey },
        requireApproval: 'never',
      }),
    ],
  });

  // Keep conversation state across turns
  const conversationSession = new OpenAIConversationsSession();

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

  console.log('\nComposio Tool Router session created.');
  console.log('\nChat started. Type your requests below.');
  console.log("Commands: 'exit', 'quit', or 'q' to end\n");

  try {
    const first = await run(agent, 'What can you help me with?', { session: conversationSession });
    console.log(`Assistant: ${first.finalOutput}\n`);
  } catch (e) {
    console.error('Error:', e instanceof Error ? e.message : e, '\n');
  }

  rl.prompt();

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

    if (['exit', 'quit', 'q'].includes(text.toLowerCase())) {
      console.log('Goodbye!');
      rl.close();
      process.exit(0);
    }

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

    try {
      const result = await run(agent, text, { session: conversationSession });
      console.log(`\nAssistant: ${result.finalOutput}\n`);
    } catch (e) {
      console.error('Error:', e instanceof Error ? e.message : e, '\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

This was a starter code for integrating Figma MCP with OpenAI Agents SDK to build a functional AI agent that can interact with Figma.

Key features:

  • Hosted MCP tool integration through Composio's Tool Router
  • SQLite session persistence for conversation history
  • Simple async chat loop for interactive testing
You can extend this by adding more toolkits, implementing custom business logic, or building a web interface around the agent.
TOOLS

Supported Tools

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

Add a comment to a file

Posts a new comment to a Figma file or branch, optionally replying to an existing root comment (replies cannot be nested); `region_height` and `region_width` in `client_meta` must be positive if defining a comment region.

Add a reaction to a comment

Posts a specified emoji reaction to an existing comment in a Figma file or branch, requiring valid file_key and comment_id.

Create a webhook

Creates a Figma webhook to receive POST notifications when specific events occur.

Create dev resources

Creates and attaches multiple uniquely-URLed development resources to specified Figma nodes, up to 10 per node.

Create, modify, or delete variables

Manages variables, collections, modes, and their values in a Figma file via batch create/update/delete operations; use temporary IDs to link new related items in one request and ensure `variableModeValues` match the target variable's `resolvedType`.

Delete a comment

Deletes a specific comment from a Figma file or branch, provided the authenticated user is the original author of the comment.

Delete a reaction

Deletes a specific emoji reaction from a comment in a Figma file; the user must have originally created the reaction.

Delete a webhook

Permanently deletes an existing webhook, identified by its unique `webhook_id`; this operation is irreversible.

Delete dev resource

Deletes a development resource (used to link Figma design elements to external developer information like code or tasks) from a specified Figma file.

Design tokens to tailwind

Convert design tokens to Tailwind CSS configuration.

Detect Background Layers

Detect background layers for selected nodes in a Figma file.

Discover Figma Resources

Smart Figma resource discovery - extract IDs from any Figma URL.

Download Figma Images

Download images from Figma file nodes.

Extract design tokens

Extract design tokens from Figma files by combining styles, variables, and node-extracted values.

Extract Prototype Interactions

Extract prototype interactions and animations from Figma files.

Get activity logs

Retrieves activity log events from Figma, allowing filtering by event types, time range, and pagination.

Get a webhook

Retrieves detailed information about a specific webhook by its ID, provided the webhook exists and is accessible to the user.

Get comments in a file

Retrieves all comments from an existing Figma file, identified by a valid `file_key`, returning details like content, author, position, and reactions, with an option for Markdown formatted content.

Get component

Fetches metadata for a specific component using its unique identifier.

Get component set

Retrieves detailed metadata for a specific published Figma component set using its unique `key`.

Get current user

Retrieves detailed information for the currently authenticated Figma user.

Get dev resources

Retrieves development resources (e.

Get file components

Retrieves published components from a Figma file, which must be a main file (not a branch) acting as a library.

Get file component sets

Retrieves all published component sets from the specified Figma main file (file_key must not be for a branch).

Get file json

Get Figma Design file data with automatic simplification.

Get file metadata

Get Figma file metadata including name, creator, last modification details, thumbnail, and access information.

Get file nodes

Fetch JSON for specific node IDs from a Figma file to avoid full-file payload limits.

Get files in a project

Fetches a list of files in a Figma project, optionally including branch metadata.

Get file styles

Retrieves a list of published styles (like colors, text attributes, effects, and layout grids) from a specified main Figma file (not a branch).

Get image fills

Retrieves temporary (14-day expiry) download URLs for all image fills in a Figma file; requires `imageRef` from `Paint` objects to map URLs.

Get library analytics component action data

Retrieves component insertion and detachment analytics for a specified Figma library, groupable by 'component' or 'team' and filterable by a date range (YYYY-MM-DD).

Get library analytics component usage data

Retrieves component usage analytics for a specified Figma library file (identified by `file_key`), with data groupable by 'component' or 'file'.

Get library analytics style action data

Retrieves style usage analytics (insertions, detachments) for a Figma library, grouped by 'style' or 'team'; if providing a date range, ensure end_date is not before start_date.

Get library analytics style usage data

Retrieves style usage analytics for a published Figma library.

Get library analytics variable action data

Retrieves weekly, paginated analytics data on variable insertions and detachments for a specified Figma library (identified by `file_key`), groupable by 'variable' or 'team', and filterable by an optional date range.

Get library analytics variable usage data

Retrieves paginated analytics data on variable usage from a specified Figma library, grouped by 'file' or 'variable', for libraries with enabled analytics.

Get local variables

Retrieves all local/remote variables for a Figma file/branch; crucial for obtaining mode-specific values which `/v1/files/{file_key}/variables/published` omits.

Get payments

Retrieves a user's payment information for a Figma plugin, widget, or Community file; the authenticated identity must own the resource.

Get projects in a team

Retrieves projects within a specified Figma team that are visible to the authenticated user.

Get published variables

Retrieves variables published from a specified Figma file; this API is available only to full members of Enterprise organizations.

Get reactions for a comment

Retrieves reactions for a specific comment in a Figma file.

Get SCIM service provider config

Get Figma's SCIM service provider configuration.

Get style

Retrieves detailed metadata for a specific style in Figma using its unique style key.

Get team components

Retrieves components published in a specific Figma team's library; the team must have published components, otherwise an empty list is returned.

Get team component sets

Retrieves a paginated list of published component sets (collections of reusable UI elements) from a specified Figma team's library.

Get team styles

Retrieves a paginated list of published styles (fill colors, text styles, effects, grids) from a specified Figma team's library.

Get webhooks

Retrieves all webhooks registered for a specified Figma context (team, project, or file).

Get versions of a file

Retrieves the version history for a Figma file or branch, as specified by its `file_key`.

Get webhook requests

Retrieves a history of webhook requests for a specific Figma webhook subscription; data is available for requests sent within the last seven days.

Render images of file nodes

Render Figma nodes as images (PNG, JPG, SVG, PDF).

Update a webhook

Updates an existing Figma webhook, identified by `webhook_id`, allowing modification of its event type, endpoint, passcode, status, or description.

Update dev resources

Updates the name and/or URL of one or more existing Figma Dev Resources, each identified by its unique `id`.

FRAMEWORKS

How to build Figma MCP Agent with another framework

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ChatGPT

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Claude Agent SDK

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Claude Code logo

Claude Code

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Claude Cowork logo

Claude Cowork

Use Figma MCP with Claude Cowork

Codex logo

Codex

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Cursor logo

Cursor

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OpenClaw logo

OpenClaw

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Hermes logo

Hermes

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CLI logo

CLI

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Google ADK logo

Google ADK

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LangChain logo

LangChain

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Vercel AI SDK logo

Vercel AI SDK

Use Figma MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Figma MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Figma MCP with LlamaIndex

CrewAI logo

CrewAI

Use Figma MCP with CrewAI

OpenCode logo

OpenCode

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VS Code logo

VS Code

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FAQ

Frequently asked questions

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

Yes, you can. OpenAI Agents SDK 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 Figma tools.

Yes, absolutely. You can configure which Figma 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 Figma data and credentials are handled as safely as possible.

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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.

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Abhi Arya
Co-founder, Opennote

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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.

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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.

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