Figma Context MCP
Give your coding agent access to your Figma data. Implement designs in any framework in one-shot.
作者による説明(英語の原文)
The Figma MCP server brings Figma design context directly into your AI workflow.
この3つを1つのスコアにまとめることはしません。意見、測定、人気はそれぞれ別のものだからです。
このサーバーのやさしい解説はまだ書いていません。以下はレジストリから読み取った事実です。
使っているAIアプリを選んで、設定をコピーしてください。
必要なもの
どのアプリを使っていますか?
上でアプリを選んでください。選んだアプリを覚えておくので、次からはボタンに「…にインストール」と表示されます。
ウェブ、デスクトップ、モバイルのClaudeで使えます:
https://mcp.figma.com/mcpターミナルでこれを実行します
claude mcp add --transport http mcp https://mcp.figma.com/mcpプロジェクトの .cursor/mcp.json、または ~/.cursor/mcp.json に貼り付けます
{
"mcpServers": {
"mcp": {
"url": "https://mcp.figma.com/mcp"
}
}
}ブラウザがアプリを開いてよいか確認し、そのあとアプリが設定を表示して確認を求めます。キーの値は空欄のままなので、自分で入力してください。
プロジェクトの .vscode/mcp.json に貼り付けます
{
"servers": {
"mcp": {
"type": "http",
"url": "https://mcp.figma.com/mcp"
}
}
}ブラウザがアプリを開いてよいか確認し、そのあとアプリが設定を表示して確認を求めます。キーの値は空欄のままなので、自分で入力してください。
ChatGPTがつなげるのは、インターネット上のサーバーだけです:
https://mcp.figma.com/mcpメニューの名前は、プランや時期によって少し違うことがあります。
選んだアプリは、この端末のCookieに保存されます。アカウントは不要です。
この設定は、作者のレジストリ登録情報から作成しています。READMEと違う場合は、READMEに従ってください。
このサーバーは、ツール一覧を表示する前にサインインを求めます。
誰でも見られる情報をチェックしており、コードは読んでいません。当てはまらない項目は数に入れていません。 · 2026年11月6日にチェック
レジストリ名はドメイン mcp.figma.com で確認済みです(レジストリがドメインの所有を確認しています)
コードの最終更新:3 日前
リポジトリにライセンスファイルが見つかりません
224ミリ秒で応答(HTTP 401)
OAuthでのサインインに対応しているため、AIアプリがログイン画面へ案内してくれます
まだチェックしていません。エンドポイントをチェックするときにツール一覧を読み取ります
レジストリでこのカテゴリにある有効なすべてのサーバーと比較しています。スターは、公開者がリポジトリの所有者である場合だけ数えます。
当てはまる基本チェック5項目のうち4項目に合格しました。コードは読んでいません。キーやトークンを追加する前に、サーバーがどんなアクセスを求めているかを確認し、必要な権限だけを持つキーを使ってください。
レジストリには必須のキーは載っていません。ただし、最初に使うときにサインインを求めるサーバーもあります。
作者のクラウドで動きます。インストール不要でインターネット経由でつながりますが、送った内容は作者のサーバーを通ります。
GitHubリポジトリの最終更新は3 日前、最新バージョン(1.0.3)がレジストリに届いたのは13 か月前です。
Claude Desktop、Claude Code、Cursor、VS CodeなどのMCP対応アプリで使えます。URLでつながるので、リモートMCPサーバーに対応したアプリ(開発者モードのChatGPTなど)でも使えます。
同じカテゴリには:Figma Context MCP, Claude Real Video, Harness
同じカテゴリで、ほかの作者が作ったサーバー。スターの多い順。
カードの見方:★ GitHubスターi3つの柱:レビュー · チェック · 利用状況i更新=最新バージョンをレジストリに公開した日i
Give your coding agent access to your Figma data. Implement designs in any framework in one-shot.
Let any LLM watch a video locally — and search everything it has ever watched.
Start Claude Code and Codex agents the person can watch, wait for them and read their answers.
作者のリポジトリから書かれたとおりにコピーしたものです。PopNx MCPは内容を確認・推奨していません。HTML、画像、スクリプトは取り除いています。リンクはこのサイトの外へ移動します。
The Figma MCP server brings Figma directly into your workflow by providing important design information and context to AI agents generating code from Figma design files.
[!NOTE]
Rate limits apply to Figma MCP server tools that read data from Figma. Some tools, such as those that write to Figma files, are exempt from the rate limits.
Users on the Starter plan or with View or Collab seats on paid plans will be limited to up to 6 tool calls per month.
Users with a Dev or Full seat on the Professional, Organization, or Enterprise plans have per minute rate limits, which follow the same limits as the Tier 1 Figma REST API. As with Figma’s REST API, Figma reserves the right to change rate limits.
For the complete set of Figma MCP server docs, see our developer documentation. By using the Figma MCP server and the related resources (including these skills), you agree to the Figma Developer Terms. These skills are currently available as a Beta feature.
Note: We're quickly improving how Figma supports AI agents. The write to canvas feature will eventually be a usage-based paid feature, but is currently available for free during the beta period.
generate_image after asking permission and disclosing Figma AI credit usage. Generated images are uploaded with upload_assets and applied to the design.Select a Figma frame and turn it into code. Great for product teams building new flows or iterating on app features.
Pull in variables, components, and layout data directly into your IDE. This is especially useful for design systems and component-based workflows.
Boost output quality by reusing your actual components. Code Connect keeps your generated code consistent with your codebase.
Learn more about Code Connect →
Capture, import, or convert a web page into a Figma design directly from your AI coding agent.
Different MCP clients require slightly different setups. Follow the instructions below for your specific client to connect to the Figma MCP server.
⌘ Shift P to search for MCP:Add Server.HTTP.https://mcp.figma.com/mcp in the search bar. Then hit Enter.figma.mcp.json file:{
"servers": { "figma": { "type": "http", "url": "https://mcp.figma.com/mcp" } } }
⌥⌘B or ⌃⌘I and switch to Agent mode.#get_design_context to confirm that the Figma MCP server tools are available. If no tools are listed, restart VS Code.[!NOTE]
You must have GitHub Copilot enabled on your account to use MCP in VS Code.
For more information, see VS Code's official documentation.
The recommended way to set up the Figma MCP server in Cursor is by installing the Figma Plugin, which includes MCP server settings as well as Agent Skills for common workflows.
Install the plugin by typing the following command in Cursor's agent chat:
/add-plugin figma
The plugin includes:
Manual setup
{
"mcpServers": { "figma": { "url": "https://mcp.figma.com/mcp" } } }
For more information, see Cursor's official documentation.
The recommended way to set up the Figma MCP server in Claude Code is by installing the Figma Plugin, which includes MCP server settings as well as Agent Skills for common workflows.
Run the following command to install the plugin from Anthropic's official plugin marketplace.
claude plugin install figma@claude-plugins-official
Learn more about Anthropic's Claude Code Plugins and Agent Skills.
Manual setup
claude mcp add --transport http figma https://mcp.figma.com/mcp
claude mcp list
claude mcp get my-server
claude mcp remove my-server
For more information, see Anthropic's official documentation.
Install the Figma extension for Gemini CLI by running the following command:
gemini extensions install https://github.com/figma/mcp-server-guide
Once installed, authenticate with Figma by running gemini and then executing the following command within the CLI:
/mcp auth figma
To uninstall the extension:
gemini extensions uninstall figma
Other code editors and tools that support Streamable HTTP can also connect to the Figma MCP server.
If you're using a different editor or tool, check its documentation to confirm it supports Streamable HTTP based communication. If it does, you can manually add the Figma MCP server using this configuration:
{
"mcpServers": { "figma": { "url": "https://mcp.figma.com/mcp" } } }
The Figma MCP server introduces a set of tools that help LLMs translate designs in Figma. Once connected, you can prompt your MCP client to access a specific design node.
To provide Figma design context to your AI client:
[!NOTE]
Your client won't be able to navigate to the selected URL, but it will extract the node-id that is required for the MCP server to identify which object to return information about.
Figma maintains a list of tools provided by the Figma MCP server in the developer documentation.
You can also learn more about the skills included with the Figma plugin for supported agents in the Figma Help Center. Depending on the agent, you may also see the terms connector, extension, or power; these include the same set of skills.
This repo also contains standalone workflow skills that are not bundled with the Figma plugin:
workflow-skills/video-interaction-mapper: Turns UI recordings into annotated Figma storyboardsworkflow-skills/generate-project-plan: Turn a PRD (plus optional codebase grounding) into a FigJam project plan boardThe quality of the generated code depends on several factors. Some controlled by you, and some by the tools you're using. Here are some suggestions for clean, consistent output.
Provide the best context for your design intent, so the MCP and your AI assistant can generate code that's clear, consistent, and aligned with your system.
CardContainer, not Group 5)[!TIP]
Resize the frame in Figma to check that it behaves as expected before generating code.
MCP gives your AI assistant structured Figma data, but your prompt drives the result. Good prompts can:
src/components/ui)Examples:
src/components/ui components"src/components/marketing/PricingCard.tsx"Stack layout component"Think of prompts like a brief to a teammate. Clear intent leads to better results.
The MCP supports different tools, and each one provides your AI assistant with a different kind of structured context. Sometimes, the assistant doesn't automatically pick the right one, especially as more tools become available. If results are off, try being explicit in your prompt.
For example, if you're getting raw code instead of tokens, try something like:
Set project-level guidance to keep output consistent—just like onboarding notes for a new developer. These are things like:
You can provide this in whatever format your MCP client uses for instruction files.
Examples:
## Figma MCP Integration Rules
These rules define how to translate Figma inputs into code for this project and must be followed for every