Figma Context MCP
Give your coding agent access to your Figma data. Implement designs in any framework in one-shot.
제작자가 쓴 설명(영어 원문)
The Figma MCP server brings Figma design context directly into your AI workflow.
이 세 가지는 절대 하나의 점수로 합치지 않아요. 의견, 측정, 인기는 서로 다른 것이니까요.
이 서버는 아직 쉬운 말로 된 요약을 쓰지 못했어요. 아래는 레지스트리에서 읽어 온 사실이에요.
쓰고 있는 AI 앱을 고른 다음 설정을 복사하세요.
필요한 것
어떤 앱을 쓰세요?
위에서 앱을 고르세요. 기억해 두었다가 다음부터는 버튼에 “…에 설치”라고 표시해요.
웹, 데스크톱, 모바일의 Claude에서 쓸 수 있어요:
https://mcp.figma.com/mcp터미널에서 이 명령어를 실행하세요
claude mcp add --transport http mcp https://mcp.figma.com/mcp프로젝트의 .cursor/mcp.json 또는 ~/.cursor/mcp.json에 붙여 넣으세요
{
"mcpServers": {
"mcp": {
"url": "https://mcp.figma.com/mcp"
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
프로젝트의 .vscode/mcp.json에 붙여 넣으세요
{
"servers": {
"mcp": {
"type": "http",
"url": "https://mcp.figma.com/mcp"
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
ChatGPT는 인터넷에 있는 서버에만 연결할 수 있어요:
https://mcp.figma.com/mcp메뉴 이름은 요금제나 시기에 따라 조금 다를 수 있어요.
선택한 앱은 이 기기의 쿠키에만 저장돼요. 계정은 필요 없어요.
이 설정은 제작자의 레지스트리 정보로 만들었어요. README와 다르면 README를 따르세요.
서버가 도구 목록을 보여 주기 전에 로그인을 요구해요.
누구나 볼 수 있는 정보를 점검했고, 코드는 읽지 않았어요. 해당하지 않는 항목은 개수에서 뺐어요. · 2026년 11월 6일 점검
레지스트리 이름이 도메인 mcp.figma.com 기준으로 확인되었어요(레지스트리가 도메인 소유를 확인해요)
코드 마지막 변경: 3일 전
저장소에서 라이선스 파일을 찾지 못했어요
224ms 만에 응답(HTTP 401)
OAuth 로그인을 지원한다고 밝혀서, AI 앱이 로그인 화면으로 안내해 줘요
아직 점검하지 않았어요. 엔드포인트를 점검할 때 도구 목록을 읽어요
레지스트리에서 이 카테고리의 활성 서버 전체와 비교했어요. 스타는 게시자가 저장소를 소유한 경우에만 세요.
해당하는 기본 점검 5개 중 4개를 통과했어요. 코드는 읽지 않았어요. 키나 토큰을 넣기 전에 서버가 어떤 권한을 요구하는지 확인하고, 꼭 필요한 권한만 있는 키를 쓰세요.
레지스트리에 필수 키가 나와 있지 않아요. 다만 처음 쓸 때 로그인을 요구하는 서버도 있어요.
제작자의 클라우드에서 실행돼요. 설치 없이 인터넷으로 연결하지만, 보내는 내용은 제작자의 서버를 거쳐요.
GitHub 저장소는 마지막으로 3일 전 변경됐고, 최신 버전(1.0.3)은 13개월 전 레지스트리에 올라왔어요.
Claude Desktop, Claude Code, Cursor, VS Code처럼 MCP를 지원하는 앱에서 쓸 수 있어요. URL로 연결되기 때문에, 원격 MCP 서버를 지원하는 앱(예: 개발자 모드의 ChatGPT)에서도 쓸 수 있어요.
같은 카테고리에는: Figma Context MCP, Claude Real Video, Harness
같은 카테고리에서 다른 제작자가 만든 서버예요. 스타 순으로 정렬했어요.
카드 보는 법:★ GitHub 스타i세 기둥: 리뷰 · 점검 · 사용 정도i업데이트 = 최신 버전을 레지스트리에 공개한 날i
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.
제작자의 저장소에서 쓰인 그대로 가져왔어요. PopNx MCP가 검토하거나 보증한 내용이 아니에요. HTML, 이미지, 스크립트는 제거했어요. 링크를 누르면 이 사이트를 벗어나요.
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