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)
Generate video, images, audio and speech with Vidofy — Veo 3.1, Kling 3.0, Flux 2 and 570+ models.
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。
VIDOFY_TOKEN「秘密」と表示された値は、あなたのアカウントの鍵です。絶対に人に教えたり、チャットに貼り付けたりしないでください。
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。
ウェブ、デスクトップ、モバイルのClaudeで使えます:
https://vidofy.ai/mcp-appClaude Desktop → Settings → Developer → Edit Config を開き、claude_desktop_config.json にこれを貼り付けます
{
"mcpServers": {
"vidofy": {
"command": "npx",
"args": [
"-y",
"@vidofy/mcp"
],
"env": {
"VIDOFY_TOKEN": "your-value"
}
}
}
}ターミナルでこれを実行します
claude mcp add --transport http vidofy https://vidofy.ai/mcp-appclaude mcp add vidofy --env VIDOFY_TOKEN=your-value -- npx -y @vidofy/mcp動かす前に、空欄の値を入力してください。
プロジェクトの .cursor/mcp.json、または ~/.cursor/mcp.json に貼り付けます
{
"mcpServers": {
"vidofy": {
"url": "https://vidofy.ai/mcp-app"
}
}
}プロジェクトの .cursor/mcp.json、または ~/.cursor/mcp.json に貼り付けます
{
"mcpServers": {
"vidofy": {
"command": "npx",
"args": [
"-y",
"@vidofy/mcp"
],
"env": {
"VIDOFY_TOKEN": "your-value"
}
}
}
}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": {
"vidofy": {
"type": "http",
"url": "https://vidofy.ai/mcp-app"
}
}
}プロジェクトの .vscode/mcp.json に貼り付けます
{
"servers": {
"vidofy": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@vidofy/mcp"
],
"env": {
"VIDOFY_TOKEN": "your-value"
}
}
}
}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。
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:
https://vidofy.ai/mcp-appメニューの名前は、プランや時期によって少し違うことがあります。
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。
このサーバーのツール一覧はまだ読み取っていません。エンドポイントは順番にチェックしています。
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
レジストリ名はドメイン vidofy.ai で確認済みです(レジストリがドメインの所有を確認しています)
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
まだチェックしていません。エンドポイントは順番にチェックしています
まだチェックしていません。エンドポイントは順番にチェックしています
まだチェックしていません。エンドポイントをチェックするときにツール一覧を読み取ります
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。
入力が必要なもの:VIDOFY_TOKEN
どちらでも使えます。パソコンにインストールしても、クラウド版につないでもかまいません。
GitHubリポジトリの最終更新は–、最新バージョン(0.1.3)がレジストリに届いたのは11 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。URLでつながるので、リモートMCPサーバーに対応したアプリ(開発者モードのChatGPTなど)でも使えます。
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。
MCP server for [Vidofy](https://vidofy.ai) — generate images, video, audio and speech from Claude, ChatGPT, VS Code, Gemini CLI, Cursor, Hermes, or any MCP client, billed to your own Vidofy account, at the same prices the website charges.
Over 570 models, including Veo 3.1, Kling 3.0, Flux 2, Seedance 2.5, Wan 2.7, Hailuo 2.3, Runway, Luma Ray 2, Qwen Image 3.0, Vidu Q3 and LTX 2 — text-to-video, image-to-video, text-to-image, image editing, video and photo effects, lipsync, text-to-speech and voice cloning. The agent browses the catalogue, prices a generation before running it, and follows one to its result.
Status: first public release.
This server is for personal Vidofy accounts. It takes one credential,
VIDOFY_TOKEN, and spends your own coins — the same balance the website
spends, at the same prices. There is no other billing mode:
VIDOFY_API_KEYis
refused at startup, and that is a decision, not a feature waiting on a release.
| Tool | What it does | Spends |
|---|---|---|
list_modes | What Vidofy can generate: text-to-image, image-to-video, lipsync, speech… | no |
list_models | The models in one mode, with each one's credit cost and rough duration | no |
get_model | One model's full input contract: a JSON Schema, its file slots and their limits | no |
estimate_cost | What a generation will cost, before running it | no |
| `generate` | Runs it. The only tool that spends the balance. | yes |
get_status | Whether a generation has finished | no |
get_result | The finished media | no |
get_balance | Coins left, and how many expire with the subscription | no |
get_usage | Recent generations and what they cost | no |
The usual order is list_modes → list_models → get_model → estimate_cost → generate → get_status → get_result.
generate is the only tool without readOnlyHint, which is what tells a client to ask the user before running it. It charges at submit, not on success, and returns immediately with an id — a generation takes from ~30 seconds to several minutes, so the agent polls get_status rather than holding the call open. Output is private by default; pass public: true only when the user asked for a permanent public link.
File inputs take a path on the machine running the server. The package reads the user's own file and streams it with the submit — it never makes a temporary copy — and checks the extension and size against that model's own limits first, so a file the server would reject never leaves the disk.
Not exposed, deliberately: checkout, auto top-up, purchases, referrals, the daily reward. Nothing in this package can buy coins or change a plan, however it is prompted.
There are two ways in. Take the first one unless your client cannot do it.
Give your client this URL:
https://vidofy.ai/mcp-app
You sign in in your browser and approve once. No token to copy, nothing to keep in a config file, and nothing to update when this package changes.
| Client | How |
|---|---|
| Claude.ai · Claude Desktop | Settings → Connectors → *Add custom connector* → paste the URL → Connect, then approve the sign-in. They share one list: add it in either and it appears in both. Available on every plan, including Free — where you get one connector. |
| ChatGPT | Settings → Connectors → add a custom connector (no such option? turn on Developer Mode in Settings first) → paste the URL → Connect, then approve. On a Business or Enterprise workspace an administrator adds it for everyone. |
| VS Code | Add an MCP server of type http with the URL above, then approve the sign-in in your browser. VS Code identifies itself with its own published client metadata, so there is nothing to register and no client secret to obtain. |
| Claude Code · Codex · Cursor | Each accepts a remote MCP server URL. Follow that client's own MCP documentation and give it the URL above. |
Then ask it: *"list Vidofy modes"* to confirm the connection, and *"make me a 5-second clip of a red bicycle"* — it prices the generation before running it.
Some clients cannot take this route, and it is worth knowing why before you try. Signing in here needs a client that identifies itself with a published metadata document — an https URL the authorization server fetches. Clients that instead expect to register themselves at a registration_endpoint, or to be handed a client_id and client_secret you created by hand, have nothing to work with: this server issues neither. Gemini CLI and Hermes are both in that group today. Take route 2 — it is not a lesser path, just a different way of proving who you are.
Create a personal MCP token at vidofy.ai → Studio → Account → MCP Access. It is shown once.
// claude_desktop_config.json (Cursor: .cursor/mcp.json — same shape)
{ "mcpServers": { "vidofy": { "command": "npx", "args": ["-y", "@vidofy/mcp"], "env": { "VIDOFY_TOKEN": "vmt_..." } } } }
npx fetches it on first run. Prefer a pinned copy? npm i -g @vidofy/mcp, then:
{ "command": "vidofy-mcp", "env": { "VIDOFY_TOKEN": "vmt_..." } }
The entry is the same everywhere — the file it goes in, and what the outer key is called, are not. Check yours against your client's own documentation before you paste:
| Client | File | Outer key |
|---|---|---|
| Claude Desktop | claude_desktop_config.json | mcpServers |
| Cursor | .cursor/mcp.json | mcpServers |
| Gemini CLI | settings.json, user-level or per project | mcpServers |
| VS Code | .vscode/mcp.json, or the user-profile mcp.json | `servers` — and each entry adds "type": "stdio" |
| Hermes | config.yaml in the Hermes home directory | mcp_servers — YAML, not JSON |
So VS Code wants:
// .vscode/mcp.json
{ "servers": { "vidofy": { "type": "stdio", "command": "npx", "args": ["-y", "@vidofy/mcp"], "env": { "VIDOFY_TOKEN": "vmt_..." } } } }
and Hermes wants the same thing in YAML:
mcp_servers:
vidofy: command: npx args: ["-y", "@vidofy/mcp"] env: VIDOFY_TOKEN: "vmt_..."
Both paths reach the same account, the same models and the same balance. The difference is only where the process runs and how you prove who you are.
One client shows more than the others. A generation normally comes back as text the model reads out. A host that supports MCP Apps gets a live card instead — the picture or clip itself, its progress while it runs, and a download button — and the server offers it only to a host that says it can render one. Claude and VS Code both do (in VS Code, turn on chat.mcp.apps.enabled). Everywhere else the same result arrives as text and, for an image, an inline picture. Nothing is missing; it is just quieter.
| Variable | Required | What it does |
|---|---|---|
VIDOFY_TOKEN | yes | Personal MCP token (vmt_…). Spends your own Vidofy coins, exactly as the studio does. |
VIDOFY_API_BASE | no | Override the origin the server talks to — an origin only, no path. Defaults to https://vidofy.ai, which is what you want. |
VIDOFY_API_KEY is recognised only in order to be refused: a vky_… key bills a different balance, which this server does not serve. Setting it stops startup with a message naming the token to use instead — and setting *both* is refused too, since the two bill different balances and no precedence rule is worth having to remember.
npm install
npm run build npm run inspect # MCP Inspector — spends nothing
VIDOFY_API_BASE points it at a different origin, if you are running one.
Nothing here writes to stdout. With stdio transport, stdout *is* the protocol channel — a single stray console.log() puts a non-JSON line in the stream and the client drops the connection with an error that explains nothing. Diagnostics go to stderr via the log() helper in src/index.ts.
src/config.ts credential + mode + base URL, validated at startup
src/backend.ts the only place that talks HTTP: auth, retries, multipart, errors src/schema.ts one model's m_options → a JSON Schema the agent can fill in src/map/b2c.ts both response shapes → one; strips the provider cost src/tools/info.ts list_modes, list_models, get_model src/tools/generation.ts estimate_cost, generate, get_status, get_result src/tools/account.ts get_balance, get_usage src/index.ts the server: stdio transport, tool registration, annotations
server.json MCP registry manifest (name must match package.json "mcpName")
MIT