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)
Render App Store and Google Play screenshots from layouts and image files via the AppScreen API.
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": {
"shotframe": {
"command": "npx",
"args": [
"-y",
"@reneturcios/shotframe",
"mcp"
]
}
}
}在终端中运行这条命令
claude mcp add shotframe -- npx -y @reneturcios/shotframe mcp粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"shotframe": {
"command": "npx",
"args": [
"-y",
"@reneturcios/shotframe",
"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": {
"shotframe": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@reneturcios/shotframe",
"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6日
注册名称已通过 GitHub 账户 CloudCorpRecords 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(0.1.0)于3天前进入注册中心。
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, Docker。
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。
Need App Store or Google Play screenshots for a store listing? shotframe hands the AppScreen API a set of screen layouts plus the image files they reference, and gives you back either a render job you can poll or a direct download link for the finished screenshots.
How a render flows:
screens — the layouts, as JSON objects. Their structure is defined by the AppScreen API; shotframe passes them through untouched and cannot validate them for you.files — the images the layouts use. Each item names a file and carries exactly one source: a local path (the client reads the bytes off disk and encodes them; a leading ~/ expands to your home directory) or inline base64 (meant only for tiny synthetic test images). An unreadable path fails the call before any request is made.jobId for keyed/async renders or a download link for anonymous/inline ones, plus balance and cost when reported. Quota metadata the API reports is surfaced on the MCP result's _meta (quota, and balance / cost / upgradeUrl when present).Poll a job with its jobId to learn its status and, when it is done, get a signed download URL. Signed URLs expire after about an hour; poll again to refresh one.
The API key is optional — anonymous use works, capped by the service at 5 lifetime renders:
export APPSCREEN_API_KEY="your key" # optional
Rendering spends your own AppScreen workspace credits; when they run out the API answers 402 and the tool reports it as an insufficient_credits error carrying the API's cost and balance text. shotframe itself holds no payment instrument.
Other environment variables:
APPSCREEN_BASE_URL — API base URL (https://api.appscreen.co by default)APPSCREEN_MCP_CLIENT — sent as the X-MCP-Client header, identifying the calling clientnpx @reneturcios/shotframe render_screenshots '{"screens":[{"device":"iphone"}], "files":[{"name":"icon.png","path":"~/shots/icon.png"}]}'
npx @reneturcios/shotframe get_render_status '{"job_id":"job-123"}' npx @reneturcios/shotframe --version
Output is the API result body as JSON. Exit codes: 0 on success, 1 on a runtime error (including a validation failure, an unreadable file, or an upstream error), 2 on a usage error.
npx -y @reneturcios/shotframe mcp
MCP client config:
{
"mcpServers": { "shotframe": { "command": "npx", "args": ["-y", "@reneturcios/shotframe", "mcp"], "env": { "APPSCREEN_API_KEY": "your key" } } } }
render_screenshots — Render App Store and Google Play screenshots from screens (layout JSON) and image files. Returns a jobId for keyed/async renders or a download link for anonymous/inline renders. screens is required; files is optional.get_render_status — Poll a render job by jobId. Returns the status and a signed download URL when done. Signed URLs expire after about an hour; re-poll to refresh.docker run -i -e APPSCREEN_API_KEY="your key" ghcr.io/cloudcorprecords/shotframe
docker run --rm ghcr.io/cloudcorprecords/shotframe get_render_status '{"job_id":"job-123"}'
npm install
npm run build # tsc -> dist/ npm test # tsx --test test/*.test.ts (fake fetch + temp files, no network) npm run dev # run the CLI from source
MIT — Copyright (c) 2026 Rene Turcios