How to integrate Figma MCP with OpenAI Agents SDK

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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, create a webhook for figma team events 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.

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 open-ai-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.

Supported Tools & Triggers

Tools
Add a comment to a filePosts 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 commentPosts a specified emoji reaction to an existing comment in a figma file or branch, requiring valid file key and comment id.
Create a webhookCreates a figma webhook for a `team id` to send post notifications for an `event type` to a publicly accessible https `endpoint`; an initial ping is sent unless `status` is `paused`.
Create dev resourcesCreates and attaches multiple uniquely-urled development resources to specified figma nodes, up to 10 per node.
Create, modify, or delete variablesManages 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 commentDeletes a specific comment from a figma file or branch, provided the authenticated user is the original author of the comment.
Delete a reactionDeletes a specific emoji reaction from a comment in a figma file; the user must have originally created the reaction.
Delete a webhookPermanently deletes an existing webhook, identified by its unique `webhook id`; this operation is irreversible.
Delete dev resourceDeletes 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 tailwindConvert design tokens to tailwind css configuration.
Detect backgroundDetect background layers for selected nodes.
Discover Figma Resources🔍 smart figma resource discovery - never guess ids again!
Download Figma ImagesDownload images from figma file nodes.
Extract design tokensExtract design tokens from figma files.
Extract Prototype InteractionsExtract prototype interactions and animations from figma files.
Get activity logsRetrieves activity log events from figma, allowing filtering by event types, time range, and pagination.
Get a webhookRetrieves detailed information about a specific webhook by its id, provided the webhook exists and is accessible to the user.
Get comments in a fileRetrieves 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 componentGet component data with automatic simplification.
Get component setRetrieves detailed metadata for a specific published figma component set using its unique `key`.
Get current userRetrieves detailed information for the currently authenticated figma user.
Get dev resourcesRetrieves development resources (e.
Get file componentsRetrieves published components from a figma file, which must be a main file (not a branch) acting as a library.
Get file component setsRetrieves all published component sets from the specified figma main file (file key must not be for a branch).
Get file jsonGet figma file data with automatic simplification.
Get files in a projectFetches a list of files in a figma project, optionally including branch metadata.
Get file stylesRetrieves a list of published styles (like colors, text attributes, effects, and layout grids) from a specified main figma file (not a branch).
Get image fillsRetrieves 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 dataRetrieves 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 dataRetrieves 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 dataRetrieves 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 dataRetrieves style usage analytics for a figma library (specified by a valid `file key`), allowing data to be grouped by 'file' or 'style'.
Get library analytics variable action dataRetrieves 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 dataRetrieves paginated analytics data on variable usage from a specified figma library, grouped by 'file' or 'variable', for libraries with enabled analytics.
Get local variablesRetrieves all local/remote variables for a figma file/branch; crucial for obtaining mode-specific values which `/v1/files/{file key}/variables/published` omits.
Get paymentsRetrieves a user's payment information for a figma plugin, widget, or community file; the authenticated identity must own the resource.
Get projects in a teamRetrieves projects within a specified figma team that are visible to the authenticated user.
Get published variablesRetrieves variables published from a specified figma file; this api is available only to full members of enterprise organizations.
Get reactions for a commentRetrieves reactions for a specific comment in a figma file.
Get styleRetrieves detailed metadata for a specific style in figma using its unique style key.
Get team componentsRetrieves components published in a specific figma team's library; the team must have published components, otherwise an empty list is returned.
Get team component setsRetrieves a paginated list of published component sets (collections of reusable ui elements) from a specified figma team's library.
Get team stylesRetrieves a paginated list of published styles, such as colors or text attributes, from a specified figma team's library.
Get team webhooksRetrieves all webhooks registered for a specified figma team.
Get versions of a fileRetrieves the version history for a figma file or branch, as specified by its `file key`.
Get webhook requestsRetrieves 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 nodesRenders specified nodes from a figma file as images (jpg, pdf, png, svg), returning a map of node ids to image urls (or `null` for failed nodes); images expire after 30 days and are capped at 32 megapixels (larger requests are scaled down).
Update a webhookUpdates an existing figma webhook, identified by `webhook id`, allowing modification of its event type, endpoint, passcode, status, or description.
Update dev resourcesUpdates the name and/or url of one or more existing figma dev resources, each identified by its unique `id`.

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

What is Tool Router?

Composio's Tool Router 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 Tool Router

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

How the Tool Router works

The Tool Router 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

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

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

Install dependencies

pip install composio_openai_agents openai-agents python-dotenv

Install the Composio SDK and the OpenAI Agents SDK.

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.

Import dependencies

import asyncio
import os
from dotenv import load_dotenv

from composio import Composio
from composio_openai_agents import OpenAIAgentsProvider
from agents import Agent, Runner, HostedMCPTool, SQLiteSession
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.

Set up the Composio instance

load_dotenv()

api_key = os.getenv("COMPOSIO_API_KEY")
user_id = os.getenv("USER_ID")

if not api_key:
    raise RuntimeError("COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key")

# Initialize Composio
composio = Composio(api_key=api_key, provider=OpenAIAgentsProvider())
What's happening:
  • load_dotenv() loads your .env file so OPENAI_API_KEY and COMPOSIO_API_KEY are available as environment variables.
  • Creating a Composio instance using the API Key and OpenAIAgentsProvider class.

Create a Tool Router session

# Create a Figma Tool Router session
session = composio.create(
    user_id=user_id,
    toolkits=["figma"]
)

mcp_url = 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.

Configure the agent

# Configure agent with MCP tool
agent = 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(
            tool_config={
                "type": "mcp",
                "server_label": "tool_router",
                "server_url": mcp_url,
                "headers": {"x-api-key": api_key},
                "require_approval": "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 dict includes the Composio API key for secure authentication with the MCP server.
  • require_approval: 'never' means the agent can execute Figma operations without asking for permission each time, making interactions smoother.

Start chat loop and handle conversation

print("\nComposio Tool Router session created.")

chat_session = SQLiteSession("conversation_openai_toolrouter")

print("\nChat started. Type your requests below.")
print("Commands: 'exit', 'quit', or 'q' to end\n")

async def main():
    try:
        result = await Runner.run(
            agent,
            "What can you help me with?",
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")
    except Exception as e:
        print(f"Error: {e}\n")

    while True:
        user_input = input("You: ").strip()
        if user_input.lower() in {"exit", "quit", "q"}:
            print("Goodbye!")
            break

        result = await Runner.run(
            agent,
            user_input,
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")

asyncio.run(main())
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 Runner.run().
  • The responses are printed to the console, and conversations are saved locally using SQLite.
  • Typing exit, quit, or q cleanly ends the chat.

Complete Code

Here's the complete code to get you started with Figma and open-ai-agents-sdk:

import asyncio
import os
from dotenv import load_dotenv

from composio import Composio
from composio_openai_agents import OpenAIAgentsProvider
from agents import Agent, Runner, HostedMCPTool, SQLiteSession

load_dotenv()

api_key = os.getenv("COMPOSIO_API_KEY")
user_id = os.getenv("USER_ID")

if not api_key:
    raise RuntimeError("COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key")

# Initialize Composio
composio = Composio(api_key=api_key, provider=OpenAIAgentsProvider())

# Create Tool Router session
session = composio.create(
    user_id=user_id,
    toolkits=["figma"]
)
mcp_url = session.mcp.url

# Configure agent with MCP tool
agent = 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(
            tool_config={
                "type": "mcp",
                "server_label": "tool_router",
                "server_url": mcp_url,
                "headers": {"x-api-key": api_key},
                "require_approval": "never",
            }
        )
    ],
)

print("\nComposio Tool Router session created.")

chat_session = SQLiteSession("conversation_openai_toolrouter")

print("\nChat started. Type your requests below.")
print("Commands: 'exit', 'quit', or 'q' to end\n")

async def main():
    try:
        result = await Runner.run(
            agent,
            "What can you help me with?",
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")
    except Exception as e:
        print(f"Error: {e}\n")

    while True:
        user_input = input("You: ").strip()
        if user_input.lower() in {"exit", "quit", "q"}:
            print("Goodbye!")
            break

        result = await Runner.run(
            agent,
            user_input,
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")

asyncio.run(main())

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.

How to build Figma MCP Agent with another framework

Claude Agent SDK

Claude Agent SDK

Use Figma MCP with Claude Agent SDK

Google ADK

Google ADK

Use Figma MCP with Google ADK

LangChain

LangChain

Use Figma MCP with LangChain

Vercel AI SDK

Vercel AI SDK

Use Figma MCP with Vercel AI SDK

Mastra AI

Mastra AI

Use Figma MCP with Mastra AI

LlamaIndex

LlamaIndex

Use Figma MCP with LlamaIndex

CrewAI

CrewAI

Use Figma MCP with CrewAI

FAQ

What are the differences in Tool Router MCP and Figma MCP?

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.

Can I use Tool Router MCP with OpenAI Agents SDK?

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.

Can I manage the permissions and scopes for Figma while using Tool Router?

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.

How safe is my data with Composio Tool Router?

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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ASU
Letta
glean
HubSpot
Agent.ai
Altera
DataStax
Entelligence
Rolai
Context
ASU
Letta
glean
HubSpot
Agent.ai
Altera
DataStax
Entelligence
Rolai

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