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)
Generate video and images (Veo 3.1, Grok Imagine, Nano Banana, GPT Image 2) via the GenRelay 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。
GENRELAY_API_KEY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 …”。
打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json
{
"mcpServers": {
"genrelay": {
"command": "npx",
"args": [
"-y",
"genrelay-mcp"
],
"env": {
"GENRELAY_API_KEY": "your-value"
}
}
}
}在终端中运行这条命令
claude mcp add genrelay --env GENRELAY_API_KEY=your-value -- npx -y genrelay-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": {
"genrelay": {
"command": "npx",
"args": [
"-y",
"genrelay-mcp"
],
"env": {
"GENRELAY_API_KEY": "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": {
"genrelay": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"genrelay-mcp"
],
"env": {
"GENRELAY_API_KEY": "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。
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 GitHub 账户 gaoruitech 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。
你需要填写:GENRELAY_API_KEY
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(0.1.2)于25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。
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。
MCP server for GenRelay — generate video and images from Claude Desktop, Cursor, or any MCP client.
One server, several models: Veo 3.1, Grok Imagine, Omni Flash, Nano Banana Pro/2, GPT Image 2.
Nothing to install — point your MCP client at it with npx.
Claude Desktop — claude_desktop_config.json:
{
"mcpServers": { "genrelay": { "command": "npx", "args": ["-y", "genrelay-mcp"], "env": { "GENRELAY_API_KEY": "sk-..." } } } }
Cursor — .cursor/mcp.json:
{
"mcpServers": { "genrelay": { "command": "npx", "args": ["-y", "genrelay-mcp"], "env": { "GENRELAY_API_KEY": "sk-..." } } } }
Get a key at genrelay.ai. Restart the client after editing the config.
| Tool | What it does |
|---|---|
generate_video | Text-to-video and image-to-video. Returns the clip, or a task id if it's still running |
generate_image | Image generation and editing. Returns the picture inline |
check_job | Pick up a job by task id |
list_models | What's available and what each model is for |
Then just ask:
Generate an 8-second video of a neon fox running through a rainy city at night, 1080p
Video generation takes 1–5 minutes — longer than an MCP tool call is allowed to run. So generate_video waits as long as it safely can, then hands back a task id:
Still generating — this is normal for video.
task id: task_abc123 status: in_progress progress: 35%
Call check_job with task id "task_abc123" in a minute or two.
That's a normal outcome, not a failure. The job keeps running server-side — use `check_job`, don't resubmit (resubmitting bills a second time).
Images usually finish inside the budget and come back inline.
Video
| Model | Notes |
|---|---|
veo_3_1 | Google Veo 3.1 — highest quality, with audio |
veo_3_1-fl | first/last frame — supply both endpoints |
veo_3_1-components | component-guided |
grok-imagine-video-1-5-preview | xAI Grok Imagine 1.5 |
grok-imagine-1-0-video | xAI Grok Imagine 1.0 |
omni-flash | fast, good for longer clips |
omni_flash_abra_edit | video editing from a source video |
Image — nano-banana-pro, nano-banana-2, gpt-image-2
Tiers: images 1k/2k/4k, Veo video 720p/1080p/4k. Pricing is per tier, and a size matching no tier falls back to the model's base rate — so set tier explicitly when cost matters.
| Variable | |
|---|---|
GENRELAY_API_KEY | required |
GENRELAY_BASE_URL | optional, defaults to https://genrelay.ai/v1 |
pip install genrelaynpm install genrelayopenai package at https://genrelay.ai/v1npm install
npm run build node test/smoke.mjs # boots the server and speaks MCP to it
What is genrelay-mcp? An MCP server that lets Claude Desktop, Cursor and other MCP clients generate video and images through the GenRelay API.
Which clients work? Any MCP client that can launch a stdio server with npx -y genrelay-mcp, including Claude Desktop and Cursor.
How do I get an API key? Sign up at genrelay.ai and create a key in the console. Set it as GENRELAY_API_KEY.
How is it billed? Prepaid credits in USD, pay as you go. See Pricing.
A video is still running. Do I resubmit? No. Use check_job with the task id. Resubmitting is billed again.
Where is it listed? npm and the official MCP Registry as io.github.gaoruitech/genrelay-mcp.
MIT