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Let your agent set it up

The fastest way to get started: copy this prompt into your coding agent. It walks through creating a Figma token and adding the server, and stops at the two steps you need to do yourself — signing in to Figma and copying the token.
Setup prompt

Get a Figma access token

1

Open your Figma account settings

From the home page in Figma, click your profile icon in the top left corner, then choose Settings.
The Figma profile menu open, with the Settings item highlighted
2

Generate a new token

In the settings dialog, switch to the Security tab, scroll down to Personal access tokens, and click Generate new token.
The Security tab of Figma settings, with the Generate new token link highlighted
3

Select the scopes the MCP needs

Give the token a name, set an expiration, then check every scope shown below before clicking Generate token. Figma tokens are scoped, and a token created with the defaults will not have what the MCP needs.
The Figma token scope picker with current_user:read, file_comments:read, file_comments:write, file_content:read, file_metadata:read, file_versions:read, library_assets:read, library_content:read, team_library_content:read, file_dev_resources:read, and file_dev_resources:write all checked
If you need more detailed instructions, you can find them in Figma’s documentation on access tokens.

Install in your editor or agent

The most common clients are below. For anything else, see other editors and agents.
Run this command in your terminal. See the Claude Code MCP docs for more info.

Other editors and agents

Add this to your Amazon Q Developer CLI configuration file. See the Amazon Q Developer CLI docs for more info.
Run this command in your terminal. See the Amp MCP docs for more info.
  1. Press Cmd/Ctrl+Shift+P or go to the hamburger menu in the Augment panel.
  2. Select Edit Settings.
  3. Under Advanced, click Edit in settings.json.
  4. Add the server configuration to the mcpServers array in the augment.advanced object:
Open Settings, navigate to Plugins, and enter the following configuration. See BoltAI’s documentation for more info.
Open Claude Desktop, go to Settings, then Developer, and edit your claude_desktop_config.json file. See the Claude Desktop MCP docs for more info.
  1. Open Cline in VS Code.
  2. Click the hamburger menu icon to enter the MCP Servers section.
  3. Choose the Installed tab.
  4. Click Edit Configuration and add the following:
See the Cline MCP docs for more info.
Open ~/.copilot/mcp-config.json and add the following configuration:
Add the following configuration to Repository → Settings → Copilot → Coding agent → MCP configuration. See the GitHub Copilot coding agent docs for more info.
Add this to your Crush configuration file. See the Crush MCP docs for more info.
Emdash is an orchestration layer for running multiple coding agents in parallel. Emdash does not modify your agent’s config directly — you still need to configure your coding agent (Codex, Claude Code, Cursor, etc.) to connect to Framelink MCP for Figma using the instructions for that specific agent on this page.See the Emdash repository for more information.
Factory’s droid supports MCP servers through its CLI. See the Factory MCP docs for more info.
Open the Gemini CLI settings file at ~/.gemini/settings.json and add the following to the mcpServers object. See the Gemini CLI docs for more info.
  1. In any JetBrains IDE, go to Settings → Tools → AI Assistant → Model Context Protocol (MCP).
  2. Click + Add.
  3. Click on Command in the top-left corner and select the As JSON option.
  4. Add this configuration:
  1. Click Apply to save changes.
See the JetBrains AI Assistant docs for more info.
Create .kilocode/mcp.json in your project directory with the following configuration:
You can also configure it via the Kilo Code UI under Settings → MCP Servers → Add Server.
  1. Navigate to Program (right side) → Install → Edit mcp.json.
  2. Paste the configuration:
  1. Click Save.
See LM Studio MCP support for more info.
  1. Navigate to Perplexity → Settings.
  2. Select Connectors.
  3. Click Add Connector.
  4. Select Advanced.
  5. Enter Server Name: Framelink_Figma_MCP
  6. Paste the configuration:
  1. Click Save.
See Perplexity’s MCP documentation for more info.
  1. Open the Qodo Gen chat panel in VS Code or IntelliJ.
  2. Click Connect more tools.
  3. Click + Add new MCP.
  4. Add the configuration:
See the Qodo Gen docs for more info.
You can use the CLI or add the config manually. See the Qwen Code MCP docs for more info.CLI
Manual ConfigurationOpen ~/.qwen/settings.json (user scope) or .qwen/settings.json (project scope) and add:
Add this to your Roo Code MCP configuration file. See the Roo Code MCP docs for more info.
Edit your Rovo Dev CLI MCP config:
Then add the following:
Add this to your Visual Studio MCP configuration. See the Visual Studio MCP docs for more info.
  1. Navigate to Settings → AI → Manage MCP servers.
  2. Click the + Add button.
  3. Paste the configuration:
  1. Click Save.
See the Warp MCP docs for more info.
Add this to your Windsurf MCP config file. See the Windsurf MCP docs for more info.
Add this to your Zed settings.json. See the Zed Context Server docs for more info.
  1. Go to the Zencoder menu (…).
  2. Select Agent tools.
  3. Click Add custom MCP.
  4. Add the name and configuration:
  1. Click Install.
Not listed? Most MCP clients take the same JSON. Check your editor’s docs, or join our Discord.

Windows, Bun, and Deno

On Windows, npx is a batch file (npx.cmd) and cannot be run directly by most MCP clients. Use cmd to run npx instead. In the JSON configuration above, replace "command": "npx" with "command": "cmd" and add "/c", "npx", to the beginning of the args array:
If you prefer an alternative runtime to Node.js, you can use Bun or Deno to run the MCP server. Use these in place of the npx command in your editor’s config above.Bun
Deno

Implement your first design

After configuring your IDE, you’ll be able to pull complete design data from any Figma file.
1

Copy a link to a Figma frame or group

The MCP server compresses the data it receives from the Figma API by almost 90%. Even still, complex designs can overwhelm AI agents with too much information.You can try to get your editor to implement a whole design for you, but for the most consistent results, work on one section at a time.To do that, right click on the frame or group you’d like to implement, then select Copy/Paste as and choose Copy link to selection.
The Figma right-click menu with Copy/Paste as, then Copy link to selection
2

Paste the link into your editor

Once you have a link to the Figma frame or group, you can make a request to your editor’s AI agent.A request as simple as “Implement this Figma frame” along with the link should be enough to get the agent to call the MCP’s get_figma_data function, but more context is often helpful in getting the best results.
A Figma selection link pasted into an editor chat prompt
3

Get your design

After submitting your request, your coding agent will get to work. It should call the MCP’s get_figma_data function with the link you provided. Using the information returned from this function, your agent will generate a design.
A coding agent calling the MCP get_figma_data tool and writing the resulting markup
As you can see above, the agent decided to name the classes frame-### since the Figma frames used in this example used Figma’s default naming. Since this was a very simple design without much context about the intended use of the element, the agent just went with a literal interpretation of the frame’s contents.The design, however, is complete and functional.
The implemented design rendered in a browser

Troubleshooting

There are some common issues you might run into when connecting to Figma. See the troubleshooting guide for more information.

Next steps

This MCP is simple but powerful in the right hands. If you’re ready to take your prompting skills to the next level, check out the best practices guide to learn how to use the MCP to its full potential.