Figma Context MCP
Give your coding agent access to your Figma data. Implement designs in any framework in one-shot.
Beschreibung vom Entwickler (englisches Original)
Generate images and video from text prompts across Gemini, OpenAI and Kie AI.
Diese drei werden nie zu einer Punktzahl zusammengefasst: Meinungen, Messungen und Beliebtheit sind verschiedene Dinge.
Für diesen Server haben wir noch keine Zusammenfassung in einfacher Sprache geschrieben. Unten stehen die Fakten, die wir aus der Registry gelesen haben.
Wähle die KI-App, die du nutzt, und kopiere die Einstellungen.
Du brauchst
Welche App nutzt du?
Wähle oben deine App. Wir merken sie uns, damit der Button beim nächsten Mal „In … installieren“ anzeigt.
Öffne Claude Desktop → Settings → Developer → Edit Config und füge dies in claude_desktop_config.json ein
{
"mcpServers": {
"mediagen": {
"command": "npx",
"args": [
"-y",
"mediagen"
]
}
}
}Führe das in deinem Terminal aus
claude mcp add mediagen -- npx -y mediagenIn .cursor/mcp.json in deinem Projekt oder in ~/.cursor/mcp.json einfügen
{
"mcpServers": {
"mediagen": {
"command": "npx",
"args": [
"-y",
"mediagen"
]
}
}
}Dein Browser fragt, ob er die App öffnen darf, dann zeigt die App die Einstellungen und bittet dich um Bestätigung. Schlüsselwerte bleiben leer, damit du sie selbst einträgst.
In .vscode/mcp.json in deinem Projekt einfügen
{
"servers": {
"mediagen": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"mediagen"
]
}
}
}Dein Browser fragt, ob er die App öffnen darf, dann zeigt die App die Einstellungen und bittet dich um Bestätigung. Schlüsselwerte bleiben leer, damit du sie selbst einträgst.
Dieser Server läuft auf deinem Computer, und ChatGPT kann sich nur mit Servern im Internet verbinden. Wähle eine andere App.
Deine Auswahl bleibt in einem Cookie auf diesem Gerät; kein Konto nötig.
Diese Einstellungen werden aus dem Registry-Eintrag des Entwicklers erzeugt. Wenn in der README etwas anderes steht, folge der README.
Läuft auf deinem Computer; die Tool-Liste erscheint nach der Installation in deiner KI-App.
Wir prüfen Informationen, die jeder sehen kann; den Code haben wir nicht gelesen. Checks, die nicht zutreffen, werden nicht mitgezählt. · Geprüft am 7. Nov. 2026
Der Registry-Name wurde mit dem GitHub-Konto Cripacx bestätigt, dem das Repo gehört
Dieses Repo haben wir noch nicht von GitHub gelesen
Dieses Repo haben wir noch nicht von GitHub gelesen
Dieser Server läuft auf deinem Computer; es gibt keinen Endpunkt im Internet
Läuft auf deinem Computer und nutzt stattdessen lokale Einstellungen
Läuft auf deinem Computer; Tool-Listen können wir nur von Endpunkten im Internet lesen
Verglichen mit allen aktiven Servern dieser Kategorie in der Registry. Sterne zählen nur, wenn dem Herausgeber das Repo gehört.
Er hat 1 von 1 zutreffenden Basischecks bestanden. Den Code haben wir nicht gelesen. Bevor du einen Schlüssel oder Token hinzufügst, sieh nach, welche Zugriffe der Server verlangt, und nutze einen Schlüssel, der nur die Berechtigungen hat, die du brauchst.
Die Registry nennt keinen erforderlichen Schlüssel, manche Server bitten dich aber bei der ersten Nutzung, dich anzumelden.
Er läuft auf deinem Computer. Deine KI-App startet ihn bei Bedarf, und die Daten laufen nicht über die Server des Entwicklers (außer der Server ruft selbst einen Onlinedienst auf).
Das GitHub-Repo wurde zuletzt – geändert, und die neueste Version (0.3.0) kam vor 3 Monaten in die Registry.
Apps, die MCP unterstützen, etwa Claude Desktop, Claude Code, Cursor und VS Code. Außerdem brauchst du Node.js auf deinem Computer.
In derselben Kategorie: Figma Context MCP, Claude Real Video, Figma MCP Server
Server derselben Kategorie von anderen Entwicklern, sortiert nach Sternen.
So liest du eine Karte:★ GitHub-SterneiDrei Säulen: Bewertungen · Checks · NutzungiAktualisiert = neueste Version in der Registry veröffentlichti
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.
Unverändert aus dem Repo des Entwicklers übernommen. PopNx MCP hat den Inhalt weder geprüft noch empfiehlt es ihn. HTML, Bilder und Skripte wurden entfernt. Links führen von dieser Website weg.
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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