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)
Figma MCP: list frames in a file and fetch one frame's JSON and image safely. 2 tools.
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。
FIGMA_TOKEN, FIGMA_API_BASE_URL, FIGMA_REQUEST_TIMEOUT_MS, FIGMA_MAX_JSON_BYTES, FIGMA_MAX_FRAME_BYTES, FIGMA_OUTPUT_ROOT, FIGMA_ALLOW_HTTP_FOR_TESTS标为机密的值是你账户的钥匙。千万不要分享给别人,也不要粘贴到聊天里。
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 …”。
链接指向作者自己的文件;我们不托管也不重新打包它。打开文件后,Claude Desktop 会进行安装。
在终端中运行这条命令
claude mcp add figma --env FIGMA_TOKEN=your-value --env FIGMA_API_BASE_URL=your-value --env FIGMA_REQUEST_TIMEOUT_MS=your-value --env FIGMA_MAX_JSON_BYTES=your-value --env FIGMA_MAX_FRAME_BYTES=your-value --env FIGMA_OUTPUT_ROOT=your-value --env FIGMA_ALLOW_HTTP_FOR_TESTS=your-value -- npx -y @scalably-io/figma-mcp运行前请先填写空着的值。
粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"figma": {
"command": "npx",
"args": [
"-y",
"@scalably-io/figma-mcp"
],
"env": {
"FIGMA_TOKEN": "your-value",
"FIGMA_API_BASE_URL": "your-value",
"FIGMA_REQUEST_TIMEOUT_MS": "your-value",
"FIGMA_MAX_JSON_BYTES": "your-value",
"FIGMA_MAX_FRAME_BYTES": "your-value",
"FIGMA_OUTPUT_ROOT": "your-value",
"FIGMA_ALLOW_HTTP_FOR_TESTS": "your-value"
}
}
}
}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": {
"figma": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@scalably-io/figma-mcp"
],
"env": {
"FIGMA_TOKEN": "your-value",
"FIGMA_API_BASE_URL": "your-value",
"FIGMA_REQUEST_TIMEOUT_MS": "your-value",
"FIGMA_MAX_JSON_BYTES": "your-value",
"FIGMA_MAX_FRAME_BYTES": "your-value",
"FIGMA_OUTPUT_ROOT": "your-value",
"FIGMA_ALLOW_HTTP_FOR_TESTS": "your-value"
}
}
}
}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。
FIGMA_API_BASE_URL envFIGMA_REQUEST_TIMEOUT_MS envFIGMA_MAX_JSON_BYTES envFIGMA_MAX_FRAME_BYTES envFIGMA_OUTPUT_ROOT envFIGMA_ALLOW_HTTP_FOR_TESTS env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7日
注册名称已通过域名 scalably.io 验证(注册中心会核实域名所有权)
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。
你需要填写:FIGMA_TOKEN
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(1.0.1)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, MCPB。
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。
Figma REST API MCP server. 2 tools list the top-level frames in a file and fetch one frame's rendered PNG plus its node JSON and image-fill map into a local output directory.
Claude Code:
claude mcp add figma -e FIGMA_TOKEN=your-token -- npx -y @scalably-io/figma-mcp
Codex:
codex mcp add figma --env FIGMA_TOKEN=your-token -- npx -y @scalably-io/figma-mcp
Claude Desktop: download figma-mcp.mcpb from the latest GitHub release and open it.
file_content:read scope./design/ or /file/, for example https://www.figma.com/design/AbC123xyz/My-file gives AbC123xyz. Both tools take it as file_key.FIGMA_TOKEN is not set the server still starts and lists its tools; every call then fails with FIGMA_NOT_CONFIGURED until the token is provided.fetch_frame is the only tool that writes files (so it is not marked read-only); it writes frame.png, node.json, and fills.json into a directory below the configured output root (default ./figma-output). The other tool is fully read-only.| Tool | What it does |
|---|---|
list_frames | List and optionally filter all top-level FRAME nodes in a Figma file, with exact page/name/node-id data, dimensions, and file metadata |
fetch_frame | Fetch one Figma frame and transactionally write frame.png, node.json, and a normalized image-fill map into a directory below the output root |
| Variable | Required | Purpose |
|---|---|---|
FIGMA_TOKEN | yes | Figma personal access token with file_content:read |
FIGMA_API_BASE_URL | no | Override the Figma REST API base URL (default https://api.figma.com/v1) |
FIGMA_REQUEST_TIMEOUT_MS | no | Per-request timeout in milliseconds (default 60000) |
FIGMA_MAX_JSON_BYTES | no | Upper bound on a Figma JSON response, in bytes (default 104857600) |
FIGMA_MAX_FRAME_BYTES | no | Upper bound on a downloaded frame PNG, in bytes (default 104857600) |
FIGMA_OUTPUT_ROOT | no | Directory that every fetch_frame output directory must stay below (default ./figma-output, created on first use) |
FIGMA_ALLOW_HTTP_FOR_TESTS | no | Test suite only: 1 allows a plain-HTTP loopback API base. Never set it in normal use |
Every tool returns plain JSON with status (succeeded, partial, no_op), summary, target, result, proof, warnings, recovery. Failures throw a plain error string: : .
fetch_frame renders through Figma's image API, so very large frames or extreme scale values can exceed the configured JSON or frame byte limits; lower scale or split the frame if that happens. fills.json URLs are temporary and expire within 14 days.
Each release lists the package version, the .mcpb sha256 and the production commit it was derived from in CHANGELOG.md. CI runs the tests and a clean install of the packed tarball on every push.
This server runs locally, on your machine, under your own credentials. It collects no personal data, contains no telemetry, stores nothing persistently beyond the frame bundles you explicitly fetch, and talks only to the vendor API it wraps. No third party, including Scalably, receives your data. Contact: hello@scalably.io. Canonical copy: https://scalably.io/connector-privacy.html
MIT. Copyright Scalably.