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 images and video from text prompts across Gemini, OpenAI and Kie AI.
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": {
"mediagen": {
"command": "npx",
"args": [
"-y",
"mediagen"
]
}
}
}ターミナルでこれを実行します
claude mcp add mediagen -- npx -y mediagenプロジェクトの .cursor/mcp.json、または ~/.cursor/mcp.json に貼り付けます
{
"mcpServers": {
"mediagen": {
"command": "npx",
"args": [
"-y",
"mediagen"
]
}
}
}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": {
"mediagen": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"mediagen"
]
}
}
}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7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 Cripacx 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(0.3.0)がレジストリに届いたのは3 か月前です。
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。
Give your agent image and video generation across Google Gemini, OpenAI and Kie AI — one skill, one install, no API to learn.
Say roughly what you want and let it decide the rest:
You: Make a hero image for the landing page, wide, something moody and industrial.
Agent: npx -y mediagen image "A disused loading dock at dusk, wet concrete…" --aspect-ratio 21:9 --json → ./output/image-20260823T094107Z.png
It wrote the prompt out in full, knew 21:9 rules OpenAI out, and read the path back from --json.
Or be exact, and it stops deciding:
You: Same thing with gemini-3-pro-image, 21:9, 4K, marked as AI-generated,
saved as hero.png.
Agent: npx -y mediagen image "A disused loading dock at dusk, wet concrete…" --model gemini-3-pro-image --aspect-ratio 21:9 --size 4K --output-name hero.png --json → ./output/hero.jpg
[looks at the image]
npx -y mediagen mark ./output/hero.jpg --visible-label --label-position top-right --json → ./output/hero.labelled.jpg
It marked in a second pass, after seeing where the subject ended up — and put the label on the flat roofline rather than over the loading bay.
Anything the CLI takes can be asked for in words — provider, model, aspect ratio, size, output name and directory, quality preset, video duration, an input image to edit, and whether to mark the result. Name any of them and the agent uses it as given; leave it out and it chooses, or falls back to what you configured.
npx -y skills add Cripacx/mediagen --skill mediagen
That is the whole installation. Nothing else to set up — the skill runs the CLI through npx, which fetches it on first use and caches it afterwards.
Then give it a key:
npx -y mediagen init
An interactive wizard: pick providers, enter each key without it being echoed, verify each against the live API, choose a model per provider, and set a default. One key is enough to start.
Now just ask your agent for an image.
mediagen models is there when you want to see what is available before choosingAnd what it will not do: ask you to paste an API key into the chat. On a configuration error the skill tells you to run mediagen init in your own terminal.
mediagen init covers first-time setup. To change something later:
npx -y mediagen config edit
A menu of every setting with its current value and where that value came from — provider, model, key, output directory, quality preset, and what mediagen mark does by default. Each change is written as you make it.
For CI and scripts, where there is no terminal, config set takes the same settings as arguments:
echo "$GEMINI_API_KEY" | npx -y mediagen config set gemini --stdin
npx -y mediagen config set gemini-model gemini-3-pro-image
Set the order you prefer, most preferred first:
npx -y mediagen config set provider-priority gemini,kie,openai
It is a preference, not a whitelist. A request with no --provider goes to the first provider in the order that has a key and can do the job — so a missing OpenAI key never stops something Gemini can do, and asking for video skips straight past the providers that do not make any. Naming --provider overrides all of it.
mediagen models shows the resulting order, which providers are usable, and what a request would get:
1. Google Gemini (gemini) [preferred, key from config file]
Would use: gemini-3.1-flash-image (provider default)
A request with no --provider uses gemini/gemini-3.1-flash-image.
With --json it adds wouldUse, usableProviders and providerPriority. That is what the skill has an agent read before generating, so it never picks a model from a provider you have no key for.
To check what is configured and whether the keys still work:
npx -y mediagen doctor
doctor reports, per provider, whether a key is configured, which layer it came from, and whether the provider accepts it — keeping _not configured_, _rejected_, _unreachable_ and _no cheap way to check_ distinct, because they call for four different fixes.
[!WARNING]
There is deliberately no flag that takes an API key as an argument. Arguments
land in shell history and in the process list, where they outlive the command
that used them.
Settings resolve from the environment first, then .env in the working directory, then the config file:
| Variable | Purpose |
|---|---|
GEMINI_API_KEY, OPENAI_API_KEY, KIE_API_KEY | credentials; at least one |
MEDIAGEN_PROVIDER_PRIORITY | providers in preference order |
GEMINI_MODEL, OPENAI_MODEL, KIE_MODEL | default model per provider |
MEDIAGEN_OUTPUT_DIR | where media is saved |
MEDIAGEN_QUALITY | fast, balanced, quality |
MEDIAGEN_MARK | mark output by default |
MEDIAGEN_VISIBLE_LABEL | add a visible label by default |
[!TIP]
A stale environment variable shadowing the key you just configured is the most
expensive failure this kind of tool has.
mediagen config listmarks every
shadowed value, so you can see it rather than guess.
| Provider | Images | Video | Editing | Key verification |
|---|---|---|---|---|
| Google Gemini | Nano Banana family, up to 4K | yes | yes | live probe |
| OpenAI | gpt-image family, DALL·E | — | yes | live probe |
| Kie AI | ~30 models: Flux, Imagen, Grok | — | most | no cheap probe; reported as such |
[!NOTE]
OpenAI takes pixel dimensions rather than aspect ratios and genuinely cannot
produce 16:9 — its widest image is 1536×1024, which is 3:2. Asking for 16:9 is
refused by name rather than quietly served as something else. The skill knows
this and routes wide shapes to Gemini.
A model absent from the listings is still sent to the provider, so a newly released model works before mediagen knows about it. Kie's catalogue is generated from Kie's own documentation rather than maintained by hand.
The EU AI Act splits disclosure into two duties, so mediagen mark has two independent switches:
| Flag | Duty | What it does |
|---|---|---|
| machine-readable | make it findable by tools | writes IPTC/XMP DigitalSourceType, on by default |
--visible-label | disclose it to people | composites the EU's official AI-content label |
Generating never marks. Marking is always a second command, run on the file afterwards:
npx -y mediagen image "a wide banner" --aspect-ratio 21:9 --size 2K --json
npx -y mediagen mark ./output/image-….jpg --visible-label --label-position top-left
That is not ceremony. A visible label has to go where the subject is not, and only the finished image can say where that is. The machine-readable marker is not free either: adding metadata to a JPEG or WebP means decoding and re-encoding it, so marking costs a second lossy pass — worth paying deliberately, not as a side effect of asking for an image. mediagen re-encodes at high quality to keep that cost small, but it cannot make it zero.
To have mediagen mark draw the visible label without being asked each time:
npx -y mediagen config edit # "AI marking by default"
A configured default is still overridable per run with --no-mark or --no-visible-label.
The visible label is the European Commission's own icon, published with the Code of Practice on Transparency of AI-generated Content and free to use without attribution. Two of its three variants are used: AI GENERATED by default, AI MODIFIED with --modified, for media a person made and a model altered. The light or dark version is picked from what is actually under the corner it lands in, because a label nobody can read is not a disclosure.
It sits bottom-right by default. --label-position moves it to another corner, or auto puts it wherever the image has the least detail.
[!IMPORTANT]
A visible label is never written over its source. `mediagen mark photo.png
--visible-label produces photo.labelled.png` and leaves the pixels of
photo.pngexactly as they were, while writing the machine-readable marker
into it — so whichever of the two you publish carries the disclosure. A label
placed badly can be redone from an untouched original and from nothing else.
--in-placeoverwrites if you really mean to.
The skill is a wrapper around a CLI, and the CLI stands on its own.
npx -y mediagen image "a wide banner" --aspect-ratio 21:9 --size 2K
npx -y mediagen image "make the sky stormy" --input ./photo.jpg npx -y mediagen mark ./output/image-….jpg --visible-label npx -y mediagen video "a marble rolling down a wooden track" --duration 6 npx -y mediagen models
Install it globally if you use it often enough to want the shorter command:
npm install -g mediagen
| Option | |
|---|---|
--provider | gemini, openai, kie |
--model | see mediagen models |
--input | source media to edit or transform |
--aspect-ratio | 1:1, 16:9, 9:16, … |
--size | 1K, 2K, 4K |
--duration | video only |
| --output-name | the
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