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)
Provider-neutral short-form AI video toolkit for agents: Sora, Gemini Veo, xAI/Grok, Seedance.
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。
SHORT_VIDEO_DRY_RUN, OPENAI_API_KEY, GEMINI_API_KEY, XAI_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": {
"short-video-agent-kit": {
"command": "npx",
"args": [
"-y",
"short-video-agent-kit"
],
"env": {
"SHORT_VIDEO_DRY_RUN": "your-value",
"OPENAI_API_KEY": "your-value",
"GEMINI_API_KEY": "your-value",
"XAI_API_KEY": "your-value"
}
}
}
}在终端中运行这条命令
claude mcp add short-video-agent-kit --env SHORT_VIDEO_DRY_RUN=your-value --env OPENAI_API_KEY=your-value --env GEMINI_API_KEY=your-value --env XAI_API_KEY=your-value -- npx -y short-video-agent-kit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": {
"short-video-agent-kit": {
"command": "npx",
"args": [
"-y",
"short-video-agent-kit"
],
"env": {
"SHORT_VIDEO_DRY_RUN": "your-value",
"OPENAI_API_KEY": "your-value",
"GEMINI_API_KEY": "your-value",
"XAI_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": {
"short-video-agent-kit": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"short-video-agent-kit"
],
"env": {
"SHORT_VIDEO_DRY_RUN": "your-value",
"OPENAI_API_KEY": "your-value",
"GEMINI_API_KEY": "your-value",
"XAI_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。
SHORT_VIDEO_DRY_RUN 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9日
注册名称已通过 GitHub 账户 davidmosiah 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:OPENAI_API_KEY, GEMINI_API_KEY, XAI_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(0.1.7)于5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:↓ 每周下载量i★ 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。
Short Video Agent Kit
One agent-first CLI + MCP for short-form AI video. Sora · Veo · xAI · Seedance — dry-run by default, paid generation when explicitly enabled.
⭐ If this agent-first tool helps your workflow, please star the repo. Stars make this tooling easier for other builders to discover and help Delx keep shipping open infrastructure.
🧱 Part of the Delx agent stack — 15 open-source MCP servers across body, reach and coordination.
Default is stdio. Optional Streamable HTTP — no session id, JSON responses, loopback only:
npx -y -p short-video-agent-kit short-video-mcp --http
Env: SHORT_VIDEO_MCP_HOST, SHORT_VIDEO_MCP_PORT, SHORT_VIDEO_MCP_TRANSPORT=http.
Provider-neutral short-form AI video toolkit for agents. It gives Codex, Claude, Cursor, Hermes, OpenClaw and other MCP clients one interface for building dry-run payloads and, when explicitly enabled, generating vertical video through Sora/OpenAI, Gemini Veo, xAI/Grok and Seedance/PiAPI-style providers.
Use it when an agent needs one safe interface for prompt-to-video payload validation and optional paid generation across multiple providers.
Video generation can be expensive and prompt-sensitive. This package makes agents start with safe steps:
--live or SHORT_VIDEO_DRY_RUN=false before provider callsnpm install -g short-video-agent-kit
Or run directly:
npm exec --yes --package=short-video-agent-kit -- short-video-agent-kit doctor
No API key needed to try it — generation is dry-run by default, so the kit returns the exact provider-neutral plan it *would* send without spending a credit.
Build a Sora plan for an 8-second vertical teaser:
short-video-agent-kit generate \
--provider openai_sora \ --prompt "Vertical 8-second product teaser for a minimalist water bottle, soft studio light, slow dolly-in" \ --output ./output/teaser.mp4
Real output (no provider call, no credits spent):
{
"ok": true, "dry_run": true, "next_step": "Pass --live or set SHORT_VIDEO_DRY_RUN=false to call the provider API.", "provider": "openai_sora", "endpoint": "POST /v1/videos", "payload": { "model": "sora-2", "prompt": "Vertical 8-second product teaser for a minimalist water bottle, soft studio light, slow dolly-in", "seconds": "8", "size": "720x1280" } }
Same prompt, different provider — the plan re-targets the endpoint and parameter shape for you. payload returns just the plan (no dry_run wrapper):
short-video-agent-kit payload --provider gemini_veo --prompt "Same teaser, 9:16, cinematic"
{
"provider": "gemini_veo", "endpoint": "POST /models/{model}:predictLongRunning", "payload": { "instances": [ { "prompt": "Same teaser, 9:16, cinematic" } ], "parameters": { "aspectRatio": "9:16", "durationSeconds": 8 } } }
Check which providers are wired up (keys are detected, never printed):
short-video-agent-kit doctor
{
"ok": false, "dry_run": true, "providers": { "openai_sora": { "configured": false, "env_keys": ["OPENAI_API_KEY"], "models": ["sora-2"] }, "gemini_veo": { "configured": false, "env_keys": ["GEMINI_API_KEY", "GOOGLE_API_KEY"], "models": ["veo-3.1-fast-generate-preview"] }, "xai_grok": { "configured": false, "env_keys": ["XAI_API_KEY"], "models": ["grok-imagine-video", "grok-imagine-image"] }, "seedance_piapi": { "configured": false, "env_keys": ["PIAPI_KEY", "SEEDANCE_API_KEY"], "models": ["seedance-2-fast-preview"] } }, "output_dir": "./output", "next_steps": [ "Set one provider key: OPENAI_API_KEY, GEMINI_API_KEY, XAI_API_KEY or PIAPI_KEY." ] }
When you are ready to actually render, set a provider key and re-run generate with --live (or SHORT_VIDEO_DRY_RUN=false).
short-video-agent-kit manifest --client codex
short-video-agent-kit doctor short-video-agent-kit privacy-audit short-video-agent-kit payload --provider gemini_veo --prompt-file prompt.txt short-video-agent-kit generate --provider openai_sora --prompt "Vertical product teaser" --output ./output/teaser.mp4 short-video-agent-kit generate --provider openai_sora --prompt-file prompt.txt --output ./output/teaser.mp4 --live
Supported providers:
openai_soragemini_veoxai_grokseedance_piapishort-video-mcp
HTTP transport:
SHORT_VIDEO_MCP_TRANSPORT=http short-video-mcp
Hermes-style config:
mcp_servers:
short_video: command: npx args: ["-y", "short-video-agent-kit"] sampling: enabled: false
Recommended first calls:
short_video_connection_statusshort_video_privacy_auditshort_video_build_payloadshort_video_generate| Tool | Purpose |
|---|---|
short_video_agent_manifest | Install/runtime guidance for Codex, Claude, Cursor, Hermes and OpenClaw |
short_video_connection_status | Provider readiness without API keys |
short_video_privacy_audit | Prompt, output and reference-asset boundaries |
short_video_build_payload | Provider-specific payload without paid generation |
short_video_generate | Dry-run by default, live only when explicitly requested |
Use short-video-agent-kit. First call short_video_connection_status and short_video_privacy_audit.
Build the payload before generation. Only set live=true if I explicitly confirm a paid provider call.
Copy .env.example to .env and fill only the provider keys you plan to use. .env, output/ and .agent-data/ are ignored by Git.
--live, MCP live=true, or SHORT_VIDEO_DRY_RUN=false.npm install
npm test npm run check