Figma Context MCP
Give your coding agent access to your Figma data. Implement designs in any framework in one-shot.
作者による説明(英語の原文)
Local video editing for AI agents: cut, caption, analyse, reuse viral formats. FFmpeg, no cloud.
この3つを1つのスコアにまとめることはしません。意見、測定、人気はそれぞれ別のものだからです。
このサーバーのやさしい解説はまだ書いていません。以下はレジストリから読み取った事実です。
使っているAIアプリを選んで、設定をコピーしてください。
必要なもの
どのアプリを使っていますか?
上でアプリを選んでください。選んだアプリを覚えておくので、次からはボタンに「…にインストール」と表示されます。
Claude Desktop → Settings → Developer → Edit Config を開き、claude_desktop_config.json にこれを貼り付けます
{
"mcpServers": {
"wecut": {
"command": "npx",
"args": [
"-y",
"wecut",
"mcp"
]
}
}
}ターミナルでこれを実行します
claude mcp add wecut -- npx -y wecut mcpプロジェクトの .cursor/mcp.json、または ~/.cursor/mcp.json に貼り付けます
{
"mcpServers": {
"wecut": {
"command": "npx",
"args": [
"-y",
"wecut",
"mcp"
]
}
}
}ブラウザがアプリを開いてよいか確認し、そのあとアプリが設定を表示して確認を求めます。キーの値は空欄のままなので、自分で入力してください。
プロジェクトの .vscode/mcp.json に貼り付けます
{
"servers": {
"wecut": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"wecut",
"mcp"
]
}
}
}ブラウザがアプリを開いてよいか確認し、そのあとアプリが設定を表示して確認を求めます。キーの値は空欄のままなので、自分で入力してください。
これはパソコンで動くサーバーですが、ChatGPTがつなげるのはインターネット上のサーバーだけです。ほかのアプリを選んでください。
選んだアプリは、この端末のCookieに保存されます。アカウントは不要です。
この設定は、作者のレジストリ登録情報から作成しています。READMEと違う場合は、READMEに従ってください。
パソコンで動くサーバーです。インストールすると、ツール一覧がAIアプリに表示されます。
誰でも見られる情報をチェックしており、コードは読んでいません。当てはまらない項目は数に入れていません。 · 2026年11月6日にチェック
レジストリ名は、リポジトリを所有するGitHubアカウント 13kailouis-stack で確認済みです
このリポジトリはまだGitHubから読み取っていません
このリポジトリはまだGitHubから読み取っていません
これはパソコンで動くため、インターネット上のエンドポイントはありません
パソコンで動き、代わりにローカルの設定を使います
パソコンで動くサーバーです。ツール一覧を読み取れるのは、インターネット上のエンドポイントがある場合だけです
レジストリでこのカテゴリにある有効なすべてのサーバーと比較しています。スターは、公開者がリポジトリの所有者である場合だけ数えます。
当てはまる基本チェック1項目のうち1項目に合格しました。コードは読んでいません。キーやトークンを追加する前に、サーバーがどんなアクセスを求めているかを確認し、必要な権限だけを持つキーを使ってください。
レジストリには必須のキーは載っていません。ただし、最初に使うときにサインインを求めるサーバーもあります。
あなたのパソコンで動きます。必要なときにAIアプリが起動し、データは作者のサーバーを通りません(サーバー自体がオンラインサービスを呼び出す場合を除きます)。
GitHubリポジトリの最終更新は–、最新バージョン(0.1.0)がレジストリに届いたのは14 日前です。
Claude Desktop、Claude Code、Cursor、VS CodeなどのMCP対応アプリで使えます。パソコンにNode.jsも必要です。
同じカテゴリには:Figma Context MCP, Claude Real Video, Figma MCP Server
同じカテゴリで、ほかの作者が作ったサーバー。スターの多い順。
カードの見方:★ GitHubスターi3つの柱:レビュー · チェック · 利用状況i更新=最新バージョンをレジストリに公開した日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.
作者のリポジトリから書かれたとおりにコピーしたものです。PopNx MCPは内容を確認・推奨していません。HTML、画像、スクリプトは取り除いています。リンクはこのサイトの外へ移動します。
WeCut is a free, open-source video editing engine for AI agents. The agent writes a small JSON project; wecut renders it with the FFmpeg already on the machine. It cuts, captions, reframes and mixes short-form video, and it can analyse a video that went viral and reuse its format as a template on new footage. CLI and MCP server. No cloud, no API key, no GPU, no telemetry.
Things you can ask an agent that has WeCut:
talk.mp4 and put the music under it, quieter when he speaks."npx -y wecut doctor # is FFmpeg ready?
npx -y wecut guide # the full guide for agents npx -y wecut probe media/talk.mp4 # duration, size, fps, audio npx -y wecut validate project.json # errors with JSON pointers and fix hints npx -y wecut preview project.json --at 1,5,9 # small JPG frames to look at npx -y wecut render project.json # out/clip.mp4 npx -y wecut mcp # the same, as an MCP server on stdio
Every command prints one JSON object on stdout. Exit codes: 0 ok, 2 invalid input, 3 missing dependency, 4 render failed, 5 over a limit.
WeCut Studio is an independent static web editor. Choose local clips, trim and reorder them, add text and music, then download a portable template for an agent on another device. Editing runs in the browser; rendering runs on the agent's computer. A public editor needs only static file hosting, not a rendering server. A localhost URL itself is not public.
Run python -m http.server 8770 --bind 127.0.0.1 --directory studio from this checkout and open http://127.0.0.1:8770. No build or backend is needed. The template file is shared through your agent chat; public template storage and project autosave are not included. Bundle import requires the 0.2.0 source/build; published npm 0.1.0 does not include it yet.
The quick way, for Claude Code, Claude Desktop, Codex, Cursor, Gemini CLI, Windsurf and Grok Build:
npx -y wecut setup # shows what it would change
npx -y wecut setup --apply # registers the MCP server and the skill, backs up each file it edits npx -y wecut setup --remove --apply
It only touches the clients it finds (or --client codex,cursor), keeps every other setting as it was, and reads each file back. Quit Claude Desktop before you run it: while it runs it can write its settings back and drop the entry. Run it again after updating WeCut, so the installed skill stays current. Or do it by hand:
WeCut needs FFmpeg 6 or newer with libass (npx -y wecut doctor checks it and says what to install):
sudo apt-get install -y ffmpegbrew install ffmpeg-full (the slim ffmpeg formula has no libass; WeCut finds ffmpeg-full on its own)winget install Gyan.FFmpegThen connect it to the agent you use. The MCP server works in a fixed workspace folder (--root, default: the folder it was started in); every media path is relative to it.
claude mcp add wecut -- npx -y wecut mcp
Or as a plugin, which also installs the WeCut skill:
/plugin marketplace add 13kailouis-stack/wecut
/plugin install wecut@wecut
Claude Desktop, Cursor, Windsurf, Cline, Roo Code, LM Studio and most other clients take this block in their MCP settings file. Give --root explicitly, because desktop apps start servers from an unpredictable folder.
{
"mcpServers": { "wecut": { "command": "npx", "args": ["-y", "wecut", "mcp", "--root", "/path/to/workspace"] } } }
code --add-mcp '{"name":"wecut","command":"npx","args":["-y","wecut","mcp"]}'
or in .vscode/mcp.json:
{ "servers": { "wecut": { "type": "stdio", "command": "npx", "args": ["-y", "wecut", "mcp"] } } }
codex mcp add wecut -- npx -y wecut mcp
or in ~/.codex/config.toml:
[mcp_servers.wecut]
command = "npx" args = ["-y", "wecut", "mcp"]
gemini extensions install https://github.com/13kailouis-stack/wecut
WeCut targets any agent with permission to run local programs and access the user's media. Product names do not determine compatibility: a terminal agent can use the CLI without MCP.
Grok Bot, Manus, Muse, OpenBot, Dots and Claude Duet are examples of requested integration targets, not a list of tested integrations. For each product, verify that its execution environment can run the WeCut binary and FFmpeg. A chat interface alone does not provide that access.
npx -y wecut guide # read this first: workflow, project format, templates
npx -y wecut doctor
Then follow the guide: probe, write project.json, validate, preview, render. In a fresh Linux sandbox install FFmpeg first with sudo apt-get install -y ffmpeg.
Clients that can launch a local MCP process can use wecut mcp over stdio; the client-specific examples above are not an allowlist. An HTTP-only MCP client needs a separate bridge: WeCut does not currently serve remote HTTP MCP. Browser-only agents need an execution environment before they can render. Node is needed for the npm launcher; a standalone binary does not need Node.
The skill in skills/wecut/SKILL.md teaches the workflow to agents that load skills (Claude Code, Claude apps, Codex, Cursor and others):
npx skills add 13kailouis-stack/wecut
npx -y wecut , or npm i -g wecut. npm installs only the binary for your platform (@wefluence/wecut- - ); there are no install scripts.SHA256SUMS.go build -o wecut ./cmd/wecutPrebuilt for Linux, macOS and Windows on x64 and arm64. Set WECUT_BINARY to use your own build through the npm launcher.
xfade), clip fadesgradients), like the dark fade behind captionsinset), colour washes for a stretch of the video, captions that light up word by word (reveal) with key words set apart (accent)--no-loudnorm skips it)wecut clone media/viral.mp4 --name news-card # -> recipes/news-card.json + out/clone/news-card/compare.jpg
clone turns a finished video into a template the way an editor would have built it: every cut and transition (flash, fade, dissolve, zoom, blur) at its exact time, each shot's framing (full screen, or shown whole on black or blurred bars) and push-in, the text cards with their colours, box, size, line spacing, padding, timing and entrance (fade, pop, slide or type), the caption style and position, the logo, and a talk that already plays under the opening B-roll. A steady beat is stored as beat indexes; recipe apply snaps those cuts onto replacement music. Each shot is a media slot, like a CapCut template. WeCut holds no model and no API key: it returns a review with the images and evidence behind each finding, and the agent running it looks and answers, so words, fonts, what each shot is and the kind of each transition come from real eyes and OCR is only a fallback. The comparison sheet puts the original beside the template filled with numbered stand-ins, so a person or a model can check it at a glance. People fill the slots in WeCut Studio; agents with wecut recipe apply. Details and the format: docs/clone.md. Cloning needs the 0.3.0 source/build; the published npm 0.1.0 does not have it yet.
wecut analyze media/viral.mp4 # shots, pace, hook, flashes, tempo, pauses + a frame sheet
wecut recipe list # templates: built-in and the workspace's recipes/*.json wecut recipe apply --input request.json # recipe + new clips, words, music -> project wecut recipe from-project my-edit.json --write recipes/my-style.json # "save as template"
analyze measures what a model cannot see in a transcript: where the cuts are (a white flash or a strobe counts once), how long the opening shot holds, whether cuts land on the beat, and whether the file ends with a silent platform outro. Its frame sheet, one frame per shot with timestamps, is how the agent reads the headline card, text style and framing.
A recipe (wecut.recipe/1, schema in schema/wecut.recipe.schema.json) is an edit's shape without its content: sections fed by roles (a 5 s hook with a headline card, then the body), text slots filled at apply time (with emphasis for the words to colour), caption and music style, effects on cuts. A recipe can carry its own default track, like a CapCut template; the music passed at apply time replaces it and "none" drops it. The built-in recipes copy the structure of formats that are common on Indonesian short-form video today: news-style reposts with a headline card, quote hooks, phrase-captioned vlogs, punched-in podcasts, photo slideshows.
Copy the structure, not the content: other creators' footage, wording and music stay theirs.
| Tool | Does |
|---|---|
wecut_doctor | checks FFmpeg, encoders and filters |
wecut_probe | duration, size, fps, audio of media files |
wecut_validate | checks a project; errors carry a JSON pointer and a hint |
wecut_preview | renders frames and returns them as images, so the model can look |
| wecut_render | renders M
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