Figma Context MCP
Give your coding agent access to your Figma data. Implement designs in any framework in one-shot.
作者提供的说明(英文原文)
MCP server that reads local Figma .fig files, fully offline
这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。
我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。
选择你使用的 AI 应用,然后复制设置。
你需要
你用的是哪个应用?
在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。
打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json
{
"mcpServers": {
"figme": {
"command": "npx",
"args": [
"-y",
"figme-mcp"
]
}
}
}在终端中运行这条命令
claude mcp add figme -- npx -y figme-mcp粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"figme": {
"command": "npx",
"args": [
"-y",
"figme-mcp"
]
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
粘贴到项目中的 .vscode/mcp.json
{
"servers": {
"figme": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"figme-mcp"
]
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
这个服务器在你的电脑上运行,而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。
你的选择通过 Cookie 保存在这台设备上,无需账户。
这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。
它在你的电脑上运行;安装后,工具列表会显示在你的 AI 应用中。
我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月8日
注册名称已通过 GitHub 账户 ntson9p 验证,该账户拥有此仓库
我们还没有从 GitHub 读取这个仓库
我们还没有从 GitHub 读取这个仓库
它在你的电脑上运行,没有互联网端点
在你的电脑上运行,改用本地设置
它在你的电脑上运行;我们只能读取互联网端点的工具列表
与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。
它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。
注册中心没有列出必需的密钥,不过有些服务器会在首次使用时要求你登录。
它在你的电脑上运行。你的 AI 应用会在需要时启动它,数据不会经过作者的服务器(除非它自己调用在线服务)。
GitHub 仓库最后更新于–,最新版本(1.1.1)于2个月前进入注册中心。
支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 Node.js。
同一分类中有:Figma Context MCP, Claude Real Video, Figma MCP Server
同一分类中其他作者的服务器,按星标数排序。
如何看卡片:★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间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.
The Figma MCP server brings Figma design context directly into your AI workflow.
按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。
An MCP server that lets your AI agent read Figma .fig files — offline, with no Figma account or API token.
Save a design from Figma as a .fig file, and your agent can read everything in it: layers and layout, colours, text, components, design tokens and images. figme can also draw any frame as a picture, so the agent can compare what it built with the design.
you: "what does the tab component in design.fig look like?"
fig_overview → 10 pages, 2,046 components, 273 variables, 212 images fig_find → "lv2/tab/large" is 2:1337, on page "Page 1" fig_style → display:flex, direction:row, gap:8, padding:"8px 16px", cornerRadius:4, stroke #FFFFFF bound to variable "tab/large/underline" (active #FFFFFF / inactive #333333)
fig_render draws any layer as a PNG or SVG..fig carries the schema that describes it, and figme decodes the file with that schema, so fields Figma adds later don't break it.You need Node.js 22.15 or newer.
1. Save the design as a `.fig` file. In Figma, choose File → Save local copy… If it's a Community file, click Open in Figma first.
2. Add figme to your agent. In Claude Code:
claude mcp add figme -- npx -y figme-mcp
For Cursor, VS Code, Windsurf and other clients, see Set up your client.
3. Ask. Give the full path to the file, and paste a Figma link if you have one:
Using figme, read /Users/me/Desktop/App.fig and build this frame as a React component:
https://www.figma.com/design/AbC123/App?node-id=3017-121
The agent picks the tools from there. A few more things to try:
Every client runs the same command, npx -y figme-mcp. Only the place you put it changes.
Claude Code
claude mcp add figme -- npx -y figme-mcp # this project
claude mcp add -s user figme -- npx -y figme-mcp # every project
To share the server with everyone who works on a repository, commit a .mcp.json at its root:
{
"mcpServers": { "figme": { "command": "npx", "args": ["-y", "figme-mcp"] } } }
The Claude Code extensions for VS Code and JetBrains use this same configuration. They don't read the editor's own MCP settings.
Cursor
Add this to ~/.cursor/mcp.json for every project, or to .cursor/mcp.json for one:
{
"mcpServers": { "figme": { "command": "npx", "args": ["-y", "figme-mcp"] } } }
VS Code (GitHub Copilot)
From a terminal:
code --add-mcp '{"name":"figme","command":"npx","args":["-y","figme-mcp"]}'
Or add this to .vscode/mcp.json. VS Code uses the key servers, not mcpServers:
{
"servers": { "figme": { "type": "stdio", "command": "npx", "args": ["-y", "figme-mcp"] } } }
Then switch the Chat view to Agent mode.
Windsurf
Add this to ~/.codeium/windsurf/mcp_config.json:
{
"mcpServers": { "figme": { "command": "npx", "args": ["-y", "figme-mcp"] } } }
Other clients
Any client that can start a local (stdio) MCP server works. Give it:
{ "command": "npx", "args": ["-y", "figme-mcp"] }
Config file locations change between client releases. If a path above doesn't match what you see, check your client's MCP documentation.
On Windows, some clients can't find npx by themselves. If the server doesn't start, run it through cmd:
{ "command": "cmd", "args": ["/c", "npx", "-y", "figme-mcp"] }
fig_overview reports with the name in the link, or ask the agent to find the layer by name instead..fig takes about 900 MB of RAM once parsed, and figme keeps up to 4 parsed files. On a smaller machine, keep just one: { "command": "npx", "args": ["-y", "figme-mcp", "--max-files", "1"] }
Your agent picks these on its own; you don't need to name them.
| Tool | What it gives the agent |
|---|---|
fig_overview | The pages, node counts, and how many components, variables and images the file has |
fig_tree | The layer tree under a node, a few levels at a time, instances opened |
fig_node | One layer in detail: size, position, corner radii, auto-layout, children |
fig_find | Layers whose name or text contains a string |
fig_text | All the text, with fonts and mixed styles |
fig_style | Fills, strokes, effects and typography, with auto-layout as CSS flexbox |
fig_components | The components, their properties, and how often each is used |
fig_instance | What an instance changes from its component |
fig_variables | Design tokens: every collection, mode and value |
fig_image | Embedded images, and the file's thumbnail |
fig_blob | Raw vector data, for anything the other tools don't decode |
fig_render | A PNG or SVG picture of any layer or page |
Parameters and example responses for each are in docs/tools.md.
.fig. It writes a file only when you ask fig_image or fig_render to save one..fig holds the design as it was when you saved it. When the design changes, save it again; figme picks up the new file.fig_render approximates a few effects, such as background blur and angular gradients, and skips a few things, such as emoji. Every render lists what it approximated or skipped. See docs/rendering.md.fig_blob returns their raw bytes.Issues and pull requests are welcome. CONTRIBUTING.md explains how to build from source and run the tests, and how the parser works.
MIT