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)
MCP server for Google Nano Banana (Gemini) image generation
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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.
GEMINI_API_KEYYou need
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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": {
"nano-banana": {
"command": "npx",
"args": [
"-y",
"mcp-nano-banana"
],
"env": {
"GEMINI_API_KEY": "your-value"
}
}
}
}Run this in your terminal
claude mcp add nano-banana --env GEMINI_API_KEY=your-value -- npx -y mcp-nano-bananaFill in the empty values before running it.
Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json
{
"mcpServers": {
"nano-banana": {
"command": "npx",
"args": [
"-y",
"mcp-nano-banana"
],
"env": {
"GEMINI_API_KEY": "your-value"
}
}
}
}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": {
"nano-banana": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"mcp-nano-banana"
],
"env": {
"GEMINI_API_KEY": "your-value"
}
}
}
}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.
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GEMINI_API_KEY envThese 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 8, 2026
The registry name was verified with the GitHub account codeFi, 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 (1.2.2) reached the registry 5 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:↓ Downloads per weeki★ 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.
MCP server for AI-powered image generation using Google Gemini Nano Banana models. Generate, edit, and combine images from text prompts — directly from your AI coding assistant.
npm install -g mcp-nano-banana
Set your API key:
export GEMINI_API_KEY=your-api-key
For MCP Registry publication metadata, the registry name is io.github.codeFi/mcp-nano-banana.
codex mcp add nano-banana --env GEMINI_API_KEY=your-api-key -- npx -y mcp-nano-banana@latest
Or add manually to ~/.codex/config.toml:
[mcp_servers.nano-banana]
command = "npx" args = ["-y", "mcp-nano-banana@latest"]
[mcp_servers.nano-banana.env] GEMINI_API_KEY = "your-api-key"
Add to ~/.qwen/settings.json:
{
"mcpServers": { "nano-banana": { "command": "npx", "args": ["-y", "mcp-nano-banana@latest"], "env": { "GEMINI_API_KEY": "your-api-key" } } } }
claude mcp add nano-banana -e GEMINI_API_KEY=your-api-key -- npx -y mcp-nano-banana@latest
Or add manually to ~/.claude/claude_desktop_config.json:
{
"mcpServers": { "nano-banana": { "command": "npx", "args": ["-y", "mcp-nano-banana@latest"], "env": { "GEMINI_API_KEY": "your-api-key" } } } }
For CLIs and desktop clients that use the standard mcpServers JSON format, register:
{
"mcpServers": { "nano-banana": { "command": "npx", "args": ["-y", "mcp-nano-banana@latest"], "env": { "GEMINI_API_KEY": "your-api-key" } } } }
git clone https://github.com/codeFi/mcp-nano-banana.git
cd mcp-nano-banana npm install npm run build
Then register with your MCP client:
{
"mcpServers": { "nano-banana": { "command": "node", "args": ["/path/to/mcp-nano-banana/dist/index.js"], "env": { "GEMINI_API_KEY": "your-api-key" } } } }
| Model | MCP Name | Description | Max Ref Images |
|---|---|---|---|
gemini-3-pro-image-preview | Nano Banana Pro | High quality, thinking mode, professional assets | 6 object + 5 character |
gemini-3.1-flash-image-preview | Nano Banana 2 | Fast, high-efficiency, 1:4/4:1/1:8/8:1 ratios | 10 object + 4 character |
gemini-2.5-flash-image | Nano Banana | Fastest, optimized for high-volume tasks | - |
The server defaults to Nano Banana Pro for best quality and automatically falls back to Flash on rate limits.
| Value | Approx. Pixels | Supported Models |
|---|---|---|
"512" | ~512px | Nano Banana 2 only |
"1K" | ~1024px | All models |
"2K" | ~2048px | All models |
"4K" | ~4096px | All models |
Default: "1K"
| Value | Dimensions at 1K | Common Use Case |
|---|---|---|
1:1 | 1024×1024 | Social posts, icons |
16:9 | 1344×768 | Headers, presentations |
9:16 | 768×1344 | Stories, mobile |
4:3 | 1152×896 | Desktop, photos |
3:4 | 896×1152 | Portraits |
2:3 | ~896×1344 | Print, magazines |
3:2 | ~1344×896 | Photos |
4:5 | ~896×1120 | Instagram posts |
5:4 | ~1120×896 | Instagram landscape |
21:9 | ~2048×878 | Ultra-wide banners |
1:4 | ~512×2048 | Nano Banana 2 only — tall strips |
4:1 | ~2048×512 | Nano Banana 2 only — wide strips |
1:8 | ~512×4096 | Nano Banana 2 only — extra tall |
8:1 | ~4096×512 | Nano Banana 2 only — extra wide |
generate_imageGenerate or edit images from text prompts.
| Parameter | Type | Required | Default | Description |
|---|---|---|---|---|
prompt | string | ✅ Yes | — | Text description or editing instructions |
imagePaths | string[] | No | — | Reference image paths on disk (up to 14) |
model | string | No | gemini-3-pro-image-preview | Model to use |
aspectRatio | string | No | 1:1 | See table above for all options |
resolution | string | No | 1K | 512, 1K, 2K, or 4K |
outputFormat | string | No | png | png, jpeg, webp |
outputPath | string | No | — | Save image to this file path |
Generate from text:
{
"prompt": "A sunset over mountains with dramatic lighting", "aspectRatio": "16:9", "resolution": "2K", "outputPath": "/Users/currentUser/Desktop/sunset.png" }
Edit an existing image:
{
"prompt": "Change the background to a coffee shop interior", "imagePaths": ["/Users/currentUser/photo.jpg"], "outputPath": "/Users/currentUser/edited.png" }
Combine multiple images:
{
"prompt": "Put these glasses on this person's face", "imagePaths": ["/path/to/face.jpg", "/path/to/glasses.jpg"], "outputPath": "/path/to/result.png" }
High-res wallpaper:
{
"prompt": "A futuristic cityscape at night with neon lights and rain", "aspectRatio": "16:9", "resolution": "4K", "outputPath": "/path/to/wallpaper.png" }
generate_faviconsGenerate a complete favicon package from a prompt or existing image.
| Parameter | Type | Required | Default | Description |
|---|---|---|---|---|
prompt | string | No\* | — | Icon description (required if imagePath not set) |
imagePath | string | No\* | — | Path to existing master icon image |
model | string | No | gemini-3-pro-image-preview | Model for prompt generation |
outputDir | string | No | — | Directory for individual favicon files |
outputPath | string | No | — | Save ZIP package to this path |
returnZipBase64 | boolean | No | false | Return ZIP as base64 text |
appName | string | No | My App | Manifest name |
shortName | string | No | App | Manifest short_name |
themeColor | string | No | #ffffff | Manifest theme color |
backgroundColor | string | No | #ffffff | Manifest background color |
includeReadme | boolean | No | true | Include README.md in package |
{
"prompt": "A minimalist banana icon with a soft gradient", "outputDir": "/path/to/favicon", "outputPath": "/path/to/favicon.zip", "appName": "MyBrand", "shortName": "Brand", "themeColor": "#1a1a2e", "backgroundColor": "#ffffff" }
Generated files:
favicon.ico — Multi-size icon (16/32/48px)favicon-16x16.png — Browser tabsfavicon-32x32.png — Higher-res tabsapple-touch-icon.png — iOS home screenandroid-chrome-192x192.png — Androidandroid-chrome-512x512.png — Android HDsite.webmanifest — PWA manifestHTML snippet (included in response):
<link rel="icon" href="/favicon.ico" sizes="any">
Image generation requires a paid Google AI Studio account. Approximate costs:
| Model | 1K | 2K | 4K |
|---|---|---|---|
| Nano Banana 2 | ~$0.04 | ~$0.08 | ~$0.15 |
| Nano Banana Pro | ~$0.06 | ~$0.13 | ~$0.24 |
You only pay for what you generate — no monthly minimum.
Input (reference images): png, jpg, jpeg, webp, gif Output: png, jpeg, webp
# Build TypeScript
npm run build
npm run dev
npm test
node dist/index.js
| Issue | Solution |
|---|---|
GEMINI_API_KEY is not set | Export the env var or add it to your MCP config |
429 Too Many Requests | Server auto-falls back to Flash model. Add billing to your account. |
403/402 Quota exceeded | Enable billing at Google Cloud Console |
503 Unavailable | High demand — retry in a moment. Common with 4K requests. |
| Image not updating after edit | Make sure you rebuilt the TypeScript (npm run build) |
imagePaths not found | Use absolute paths. Relative paths may not resolve correctly. |
AI Assistant (MCP Client)
│ (MCP Protocol over stdio) ▼ mcp-nano-banana Server │ (HTTPS POST) ▼ Google Gemini API │ ▼ Generated Image → saved to outputPath (or returned inline base64)
MIT