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)
Kling AI video generation MCP server for Model Context Protocol hosts
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。
KLING_ACCESS_KEY, KLING_SECRET_KEY, KLING_REQUEST_TIMEOUT_MS, MCP_WORKSPACE_PATH, KLING_DOWNLOAD_ROOT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": {
"kling": {
"command": "npx",
"args": [
"-y",
"@mindstone/mcp-server-kling"
],
"env": {
"KLING_ACCESS_KEY": "your-value",
"KLING_SECRET_KEY": "your-value",
"KLING_REQUEST_TIMEOUT_MS": "your-value",
"MCP_WORKSPACE_PATH": "your-value",
"KLING_DOWNLOAD_ROOT": "your-value"
}
}
}
}在终端中运行这条命令
claude mcp add kling --env KLING_ACCESS_KEY=your-value --env KLING_SECRET_KEY=your-value --env KLING_REQUEST_TIMEOUT_MS=your-value --env MCP_WORKSPACE_PATH=your-value --env KLING_DOWNLOAD_ROOT=your-value -- npx -y @mindstone/mcp-server-kling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": {
"kling": {
"command": "npx",
"args": [
"-y",
"@mindstone/mcp-server-kling"
],
"env": {
"KLING_ACCESS_KEY": "your-value",
"KLING_SECRET_KEY": "your-value",
"KLING_REQUEST_TIMEOUT_MS": "your-value",
"MCP_WORKSPACE_PATH": "your-value",
"KLING_DOWNLOAD_ROOT": "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": {
"kling": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@mindstone/mcp-server-kling"
],
"env": {
"KLING_ACCESS_KEY": "your-value",
"KLING_SECRET_KEY": "your-value",
"KLING_REQUEST_TIMEOUT_MS": "your-value",
"MCP_WORKSPACE_PATH": "your-value",
"KLING_DOWNLOAD_ROOT": "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。
KLING_REQUEST_TIMEOUT_MS envMCP_WORKSPACE_PATH envKLING_DOWNLOAD_ROOT 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 GitHub 账户 mindstone 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:KLING_ACCESS_KEY, KLING_SECRET_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(0.5.0)于4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。
Kling AI video and image generation MCP server for Model Context Protocol hosts. Generate AI videos from text or images, extend them, add lip-sync, generate images, and manage generation tasks through a standardised MCP interface.
KLING_ACCESS_KEY)STATUS.jsonAfter clicking the button, your host will prompt you to fill: KLING_ACCESS_KEY, KLING_SECRET_KEY, KLING_REQUEST_TIMEOUT_MS.
Manual config for Claude Desktop / Claude Code / Goose / Continue.dev (Kling)
{
"mcpServers": { "Kling": { "command": "npx", "args": [ "-y", "@mindstone/mcp-server-kling" ], "env": { "KLING_ACCESS_KEY": "", "KLING_SECRET_KEY": "", "KLING_REQUEST_TIMEOUT_MS": "60000" } } } }
cd <path-to-repo>/connectors/kling
npm install npm run build
npx -y @mindstone/mcp-server-kling
node dist/index.js
KLING_ACCESS_KEY — Kling API access keyKLING_SECRET_KEY — Kling API secret keyMCP_HOST_BRIDGE_STATE — optional path to a host bridge state file used for credential managementMINDSTONE_REBEL_BRIDGE_STATE — backwards-compatible alias for MCP_HOST_BRIDGE_STATEMCP_WORKSPACE_PATH — optional directory that local media inputs (image_path, audio_path) must live inside. Defaults to the system temp directory when unset. Files elsewhere are refused before any read.KLING_DOWNLOAD_ROOT — optional directory that download_kling_video output paths must live inside. It must itself resolve inside the workspace (MCP_WORKSPACE_PATH, or the system temp directory when unset); anything else is refused with guidance. Default: /kling-downloads (auto-created). Sensitive paths (~/.ssh, ~/.aws, /etc, shell rc files) are refused even when the root would otherwise permit them.KLING_REQUEST_TIMEOUT_MS — optional override (positive integer ms, max 30 min) for the outbound HTTP request timeout applied to both Kling API and host-bridge calls. Default: 60000 (60s). Raise this if you see TIMEOUT errors on slow submits; lower it if you want tighter bounds.{
"mcpServers": { "Kling": { "command": "npx", "args": ["-y", "@mindstone/mcp-server-kling"], "env": { "KLING_ACCESS_KEY": "your-access-key", "KLING_SECRET_KEY": "your-secret-key" } } } }
{
"mcpServers": { "Kling": { "command": "node", "args": [" /connectors/kling/dist/index.js"], "env": { "KLING_ACCESS_KEY": "your-access-key", "KLING_SECRET_KEY": "your-secret-key" } } } }
configure_kling_api_keys — Save Kling API credentialsgenerate_kling_video — Create an AI-generated video from a text descriptiongenerate_kling_image_to_video — Animate a still image into a video (public HTTPS URL or local file via image_path)extend_kling_video — Continue a generated video, adding ~4-5 seconds per callgenerate_kling_lip_sync — Make a person in a video speak, from text (text-to-speech) or an audio filegenerate_kling_image — Create an AI-generated image from a text description, with optional reference imageModels: the video tools default to kling-v2-6 and the image tool to kling-v2-1. kling-v3 (Kling 3.0) is available on all three generation tools through the model parameter; it costs about twice as many Kling units per second of video and per image, so it is not the default.
check_kling_task — Check if a generation task is complete (task types: text2video, image2video, video-extend, lip-sync, image)list_kling_tasks — List your generation tasks with paginationdownload_kling_video — Save a generated video or image to a local file (result URLs expire 30 days after generation). Only Kling result URLs (klingai.com hosts) are accepted.get_kling_balance — List resource packages on the account and their remaining quantitiesAll generation tools accept an optional callback_url (HTTPS) that Kling POSTs to on task status changes, as an alternative to polling.
FSL-1.1-MIT — Functional Source License, Version 1.1, with MIT future licence. The software converts to MIT licence on 2030-04-08.
files/readModes version 1 is an experimental extension used by these connectors, not part of the MCP standard. A compatible host (the app running the connector) decides which input files a tool call may read. The connector opens only the host-approved physical path, after resolving symlinks. The host supplies this permission information with each call; it is not a tool argument you need to set. Missing or invalid permission information, or a file absent from the approved list, stops the read.
Clients that do not negotiate this extension keep the connector's existing standalone file restrictions. This extension changes input-read permissions; existing output destinations, upload formats, size limits and file checks apply.