Figma Context MCP
Give your coding agent access to your Figma data. Implement designs in any framework in one-shot.
Description from the maker (original English)
Generate images and video from text prompts across Gemini, OpenAI and Kie AI.
These three are never merged into one score: opinions, measurements and popularity are different things.
We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.
Pick the AI app you use, then copy the settings.
You need
Which app do you use?
Pick your app above. We remember it, so next time the button says “Install in …”.
Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json
{
"mcpServers": {
"mediagen": {
"command": "npx",
"args": [
"-y",
"mediagen"
]
}
}
}Run this in your terminal
claude mcp add mediagen -- npx -y mediagenPaste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json
{
"mcpServers": {
"mediagen": {
"command": "npx",
"args": [
"-y",
"mediagen"
]
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
Paste into .vscode/mcp.json in your project
{
"servers": {
"mediagen": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"mediagen"
]
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.
Your choice stays on this device in a cookie; no account needed.
These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.
Runs on your computer; the tool list appears in your AI app after you install it.
We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 7, 2026
The registry name was verified with the GitHub account Cripacx, which owns the repo
We have not read this repo from GitHub yet
We have not read this repo from GitHub yet
This one runs on your computer; there is no internet endpoint
Runs on your computer and uses local settings instead
Runs on your computer; we can only read tool lists from internet endpoints
Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.
It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.
The registry does not list a required key, though some servers ask you to sign in on first use.
It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).
The GitHub repo last changed –, and the latest version (0.3.0) reached the registry 3 months ago.
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js on your computer.
In the same category: Figma Context MCP, Claude Real Video, Figma MCP Server
Servers in the same category from other makers, sorted by stars.
Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi
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.
Figma’s official server gives AI your design data so it can turn designs into code or describe them accurately. Connects to Figma’s cloud.
Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.
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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