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)
Check whether a video was generated by AI (Sora, Veo, Kling, HeyGen and others).
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。
Authorization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 …”。
这个地址需要在请求的 header 中放入密钥,而添加连接器的菜单无法设置。请改用 Claude Code、Cursor 或 VS Code。
在终端中运行这条命令
claude mcp add --transport http aivideocheck https://api.aivideocheck.net/mcp --header 'Authorization: Bearer {api_key}'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": {
"aivideocheck": {
"url": "https://api.aivideocheck.net/mcp",
"headers": {
"Authorization": "Bearer {api_key}"
}
}
}
}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": {
"aivideocheck": {
"type": "http",
"url": "https://api.aivideocheck.net/mcp",
"headers": {
"Authorization": "Bearer {api_key}"
}
}
}
}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。
这个地址需要在请求的 header 中放入密钥,而添加连接器的菜单无法设置。请改用 Claude Code、Cursor 或 VS Code。
你的选择通过 Cookie 保存在这台设备上,无需账户。
Authorization 机密 必填 HTTP header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。
我们还没有读取这个服务器的工具列表;我们会轮流检查各个端点。
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 aivideocheck.net 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
尚未检查;我们会轮流检查各个端点
尚未检查;我们会轮流检查各个端点
尚未检查;我们会在检查端点时读取工具列表
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:Authorization
它在作者的云端运行。通过互联网连接,无需安装,但你发送的内容会经过作者的服务器。
GitHub 仓库最后更新于–,最新版本(1.0.0)于37天前进入注册中心。
支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。它通过 URL 连接,所以接受远程 MCP 服务器的应用也可以使用,例如开启开发者模式的 ChatGPT。
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。
Let Claude, Cursor or any MCP client check whether a video was generated by AI.
This server connects your AI assistant to AI Video Check, a detector for AI-generated video (Sora, Veo, Kling, MiniMax, HeyGen and others). Give it a link or a local file, and it returns the probability of AI generation with separate scores for the picture and the sound.
It is a thin layer over the public AI Video Check API: the same key, the same credits and the same results.
| Tool | What it does | Cost |
|---|---|---|
check_video(url) | Checks the video at a public link (TikTok, Instagram, X, YouTube, Facebook or a direct file URL). Waits up to about a minute for the result. | 1 credit per started minute of video |
get_check(check_id) | Returns the result of an earlier check. Results are kept for 24 hours. | free |
get_balance() | Shows the remaining credits and the limits of your key. | free |
check_file(path) | Checks a video file on your own computer. Local mode only. | 1 credit per started minute of video |
Every result tells the assistant how to read it: a probability, not proof. A low score means no signs of generation were found, not that the video is authentic. Editing, visual effects and face swaps on real footage are not detected.
Keep the key secret. Anyone holding it spends your credits. You can revoke a key on the same page; it stops working within a minute.
The server runs at https://api.aivideocheck.net/mcp (Streamable HTTP). Your client sends the key in the Authorization header.
Claude Code
claude mcp add --transport http aivideocheck https://api.aivideocheck.net/mcp --header "Authorization: Bearer avc_live_..."
Cursor (~/.cursor/mcp.json)
{
"mcpServers": { "aivideocheck": { "url": "https://api.aivideocheck.net/mcp", "headers": { "Authorization": "Bearer avc_live_..." } } } }
Any other client that supports Streamable HTTP with custom headers works the same way.
The local server runs on your machine and can also check video files from your disk. It uploads them to AI Video Check for analysis, exactly as the website does; files are deleted when the check ends.
git clone https://github.com/aivideocheck/aivideocheck-mcp
cd aivideocheck-mcp python -m venv .venv .venv/bin/pip install -r requirements.txt # Windows: .venv\Scripts\pip
Then point your client at it, for example Claude Desktop (claude_desktop_config.json):
{
"mcpServers": { "aivideocheck": { "command": "/path/to/aivideocheck-mcp/.venv/bin/python", "args": ["/path/to/aivideocheck-mcp/avc_mcp.py"], "env": { "AVC_API_KEY": "avc_live_..." } } } }
check_file sends only files that are named and built like a video container (MP4, MOV, WebM, MKV, AVI and similar). Anything else stays on your computer, so an instruction hidden in a web page cannot make your assistant upload, say, your SSH key.
| Variable | Default | Meaning |
|---|---|---|
AVC_API_KEY | — | Your key. Read in local mode only; the remote server never uses a key from its own environment. |
AVC_API_BASE | https://api.aivideocheck.net | API address. |
AVC_MCP_WAIT_S | 55 | How long check_video waits for a result before returning the check id. |
.venv/bin/python tests/test_mcp.py
The test runs the server against a fake API on 127.0.0.1, over real HTTP and real stdio, with the MCP SDK's own client. It does not touch the live service.
Checks spend the same credits as the website: one credit per started minute of video. Prices are on the developer page. Use of the API is governed by the Terms of Service and the Privacy Policy.
Questions: support@aivideocheck.net
MIT — see LICENSE.