Figma Context MCP
Give your coding agent access to your Figma data. Implement designs in any framework in one-shot.
Descripción del creador (original en inglés)
AI image generation and editing with prompt optimization and quality presets
Estos tres nunca se combinan en una sola puntuación: las opiniones, las mediciones y la popularidad son cosas distintas.
Todavía no escribimos un resumen sencillo para este. Abajo están los datos que leímos del registro.
Elige la app de IA que usas y copia la configuración.
IMAGE_PROVIDER, GEMINI_API_KEY, OPENAI_API_KEY, ARK_API_KEY, IMAGE_OUTPUT_DIR, IMAGE_QUALITY, SKIP_PROMPT_ENHANCEMENTLos valores marcados como secretos son llaves de tu cuenta. Nunca los compartas ni los pegues en un chat.
Necesitas
¿Qué app usas?
Elige tu app arriba. La recordamos, así que la próxima vez el botón dirá “Instalar en …”.
Abre Claude Desktop → Settings → Developer → Edit Config y pega esto en claude_desktop_config.json
{
"mcpServers": {
"image": {
"command": "npx",
"args": [
"-y",
"mcp-image"
],
"env": {
"IMAGE_PROVIDER": "your-value",
"GEMINI_API_KEY": "your-value",
"OPENAI_API_KEY": "your-value",
"ARK_API_KEY": "your-value",
"IMAGE_OUTPUT_DIR": "your-value",
"IMAGE_QUALITY": "your-value",
"SKIP_PROMPT_ENHANCEMENT": "your-value"
}
}
}
}Ejecuta esto en tu terminal
claude mcp add image --env IMAGE_PROVIDER=your-value --env GEMINI_API_KEY=your-value --env OPENAI_API_KEY=your-value --env ARK_API_KEY=your-value --env IMAGE_OUTPUT_DIR=your-value --env IMAGE_QUALITY=your-value --env SKIP_PROMPT_ENHANCEMENT=your-value -- npx -y mcp-imageCompleta los valores vacíos antes de ejecutarlo.
Pégalo en .cursor/mcp.json de tu proyecto, o en ~/.cursor/mcp.json
{
"mcpServers": {
"image": {
"command": "npx",
"args": [
"-y",
"mcp-image"
],
"env": {
"IMAGE_PROVIDER": "your-value",
"GEMINI_API_KEY": "your-value",
"OPENAI_API_KEY": "your-value",
"ARK_API_KEY": "your-value",
"IMAGE_OUTPUT_DIR": "your-value",
"IMAGE_QUALITY": "your-value",
"SKIP_PROMPT_ENHANCEMENT": "your-value"
}
}
}
}Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.
Pégalo en .vscode/mcp.json de tu proyecto
{
"servers": {
"image": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"mcp-image"
],
"env": {
"IMAGE_PROVIDER": "your-value",
"GEMINI_API_KEY": "your-value",
"OPENAI_API_KEY": "your-value",
"ARK_API_KEY": "your-value",
"IMAGE_OUTPUT_DIR": "your-value",
"IMAGE_QUALITY": "your-value",
"SKIP_PROMPT_ENHANCEMENT": "your-value"
}
}
}
}Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.
Este se ejecuta en tu computadora, y ChatGPT solo puede conectarse a servidores en internet. Elige otra app.
Tu elección se guarda en una cookie en este dispositivo; no necesitas cuenta.
IMAGE_PROVIDER envIMAGE_OUTPUT_DIR envIMAGE_QUALITY envSKIP_PROMPT_ENHANCEMENT envEsta configuración se genera a partir de la ficha del creador en el registro. Si el README dice otra cosa, sigue el README.
Se ejecuta en tu computadora; la lista de herramientas aparece en tu app de IA después de instalarlo.
Revisamos información que cualquiera puede ver; no hemos leído el código. Las revisiones que no aplican no se cuentan. · Revisado el 7 nov 2026
El nombre en el registro se verificó con la cuenta de GitHub shinpr, dueña del repo
Todavía no hemos leído este repo en GitHub
Todavía no hemos leído este repo en GitHub
Este se ejecuta en tu computadora; no hay endpoint en internet
Se ejecuta en tu computadora y usa ajustes locales en su lugar
Se ejecuta en tu computadora; solo podemos leer listas de herramientas de endpoints en internet
Comparado con todos los servidores activos de esta categoría en el registro. Las estrellas solo cuentan cuando quien lo publica es dueño del repo.
Superó 1 de 1 revisiones básicas aplicables. No hemos leído el código. Antes de agregar una clave o un token, revisa qué acceso pide el servidor y usa una clave que tenga solo los permisos que necesitas.
Debes completar: GEMINI_API_KEY, OPENAI_API_KEY, ARK_API_KEY
Se ejecuta en tu computadora. Tu app de IA lo inicia cuando hace falta, y los datos no pasan por los servidores del creador (a menos que el propio servidor llame a un servicio en línea).
El repo de GitHub cambió por última vez –, y la última versión (0.19.0) llegó al registro anteayer.
Las apps compatibles con MCP, como Claude Desktop, Claude Code, Cursor y VS Code. También necesitas Node.js en tu computadora.
En la misma categoría: Figma Context MCP, Claude Real Video, Figma MCP Server
Servidores de la misma categoría hechos por otros creadores, ordenados por estrellas.
Cómo leer una tarjeta:★ Estrellas de GitHubiTres pilares: reseñas · revisiones · usoiActualizado = fecha en que se publicó la última versión en el registroi
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.
Copiado tal cual del repo del creador. PopNx MCP no lo ha revisado ni lo respalda. Se quitaron HTML, imágenes y scripts. Los enlaces llevan fuera de este sitio.
Generate and edit images from Codex, Cursor, Claude Code, or any MCP client. mcp-image adds visual direction to your request before sending it to Gemini, OpenAI, or BytePlus Seedream.
Tell it what image to create or what to change in an existing image, and what it is for. The result is saved to disk and returned to your assistant.
Before generating an image, mcp-image rewrites short requests into more specific prompts. It keeps what you asked for and fills in what the image needs for its use, such as lighting and camera angle for a photo or layout for a poster. Text you want in the image stays as you wrote it, in your language. The more detail you provide, the less it changes.
You ask:
"A photo of a roast chicken dinner for a recipe site. It should look like it was actually cooked, and it should be partway through being carved so you can tell how juicy it is."
mcp-image sends to the image model:
"... a freshly roasted whole chicken resting on a rustic, seasoned wooden carving board. The chicken features deeply bronzed, blistered, and crispy skin ... It is partway carved, with one breast cleanly sliced open to reveal tender, steaming-hot white meat glistening with natural juices pooling slightly onto the board ... shallow depth of field with a softly blurred background."
*Generated with Gemini using the default fast quality preset.*
What carried through:
for a recipe site: one clear subject, with everything else kept subordinateactually cooked: blistered, uneven browning, rising steam, and drippings on the knifepartway through being carved: one breast sliced open, with the cut piece still resting against the birdhow juicy it is: juices pooling on the board and shallow depth of field around the cutCompare the same request with prompt enhancement turned off
*Baseline from the same request, with prompt enhancement disabled.*
Set SKIP_PROMPT_ENHANCEMENT=true to send the original prompt to the image model unchanged.
You need Node.js 22 or later, an MCP-compatible client, and an API key for one image provider.
All three providers generate and edit images. Gemini is the default and requires the least configuration.
| Provider | Image size | Output format | Setup |
|---|---|---|---|
| Gemini (default) | 1K, 2K, 4K | Automatic | Get a key, then set GEMINI_API_KEY |
| OpenAI | 1K, 2K, 4K | PNG or JPEG | Get a key, then set IMAGE_PROVIDER=openai and OPENAI_API_KEY |
| BytePlus Seedream | 1K, 2K | PNG or JPEG | Get an AP region key, then set IMAGE_PROVIDER=seedream and ARK_API_KEY |
Google Search grounding is available with Gemini only. OpenAI may require organization verification before it can generate images.
The examples below use Gemini. Replace the provider settings if you prefer OpenAI or Seedream.
Add this to ~/.codex/config.toml:
[mcp_servers.mcp-image]
command = "npx" args = ["-y", "mcp-image"]
[mcp_servers.mcp-image.env] GEMINI_API_KEY = "your_gemini_api_key_here" IMAGE_OUTPUT_DIR = "/absolute/path/to/images"
Add this to ~/.cursor/mcp.json for all projects, or .cursor/mcp.json in a project:
{
"mcpServers": { "mcp-image": { "command": "npx", "args": ["-y", "mcp-image"], "env": { "GEMINI_API_KEY": "your_gemini_api_key_here", "IMAGE_OUTPUT_DIR": "/absolute/path/to/images" } } } }
Run this in your project directory:
claude mcp add mcp-image --env GEMINI_API_KEY=your-api-key --env IMAGE_OUTPUT_DIR=/absolute/path/to/images -- npx -y mcp-image
Add --scope user after mcp-image to make it available in every project.
Never commit API keys to version control. Use an absolute IMAGE_OUTPUT_DIR in MCP configuration because the server's working directory depends on the client. If omitted, images are written to ./output relative to that working directory.
Restart your MCP client after changing its configuration, then ask your AI assistant:
Generate a product photo of a ceramic coffee mug on a wooden desk.
The generated file is saved in the configured output directory and returned to the assistant as an MCP resource.
Run mcp-image from a local checkout
pnpm install
pnpm run build
Configure the MCP client to run the local build instead of npx -y mcp-image:
node /absolute/path/to/mcp-image/dist/index.js
Give the assistant an absolute path to the source image:
Edit /path/to/image.jpg so the person is facing right.
Generate a high-quality product photo of a smartphone with clear text on the screen.Generate a cinematic desert landscape in a 21:9 aspect ratio.Keep the knight's appearance consistent with the previous image.See the tool reference for the options your assistant can pass explicitly.
Changing the provider changes both prompt enhancement and image generation. The way you ask for an image stays the same.
IMAGE_QUALITY accepts fast (default), balanced, or quality. Set it in the MCP server environment:
IMAGE_QUALITY=balanced
Use fast to try ideas quickly, balanced for everyday use, and quality for complex scenes or images where small details matter. Higher settings can take longer and cost more; results vary by provider.
All three providers support these presets for generation and editing. You can override the default with the quality option on each request.
| Variable | Default | Description |
|---|---|---|
IMAGE_PROVIDER | gemini | Default provider: gemini, openai, or seedream |
GEMINI_API_KEY | - | API key for Gemini |
OPENAI_API_KEY | - | API key for OpenAI |
ARK_API_KEY | - | ModelArk AP API key for Seedream |
IMAGE_OUTPUT_DIR | ./output | Directory where generated images are saved; use an absolute path in MCP configuration |
IMAGE_QUALITY | fast | Default quality preset: fast, balanced, or quality |
SKIP_PROMPT_ENHANCEMENT | false | Set to true to send prompts through unchanged |
You can configure keys for more than one provider and switch per request. A request-level provider option takes precedence over IMAGE_PROVIDER.
Your MCP client calls this tool for you. Open the reference when you need to check an option or provider limitation.
generate_image parameters
| Parameter | Type | Required | Description |
|---|---|---|---|
prompt | string | Yes | Image description or editing instruction |
quality | string | No | fast, balanced, or quality; overrides IMAGE_QUALITY |
provider | string | No | gemini, openai, or seedream; overrides IMAGE_PROVIDER |
inputImagePaths | string[] | No | Absolute paths to input images for editing |
fileName | string | No | Output filename; .png, .jpg, or .jpeg selects the format for OpenAI and Seedream |
aspectRatio | string | No | 1:1 (default), 2:3, 3:2, 3:4, 4:3, 4:5, 5:4, 9:16, 16:9, 21:9, 1:4, 1:8, 4:1, or 8:1 |
imageSize | string | No | 1K, 2K, or 4K; availability depends on the provider |
blendImages | boolean | No | Add blending guidance when combining visual elements |
maintainCharacterConsistency | boolean | No | Keep a character's appearance consistent across images |
useWorldKnowledge | boolean | No | Add context for historical figures, landmarks, and factual scenes |
useGoogleSearch | boolean | No | Gemini only. Use Google Search grounding for current information |
purpose | string | No | Intended use, such as cookbook cover or social media post |
category | string | No | Kind of image: photo, illustration, asset, ui-screen, graphic-design, diagram, or pattern-texture. Your assistant sets it when the kind is clear |
Check that the key for the selected provider is present in the MCP server's environment:
GEMINI_API_KEYOPENAI_API_KEYARK_API_KEYRestart the MCP client after changing its configuration.
Use absolute paths and make sure the MCP server can read the files. Input images can be PNG, JPEG, or WebP and must be no larger than 10 MiB each. Seedream editing accepts PNG and JPEG only.
Check the requested size in the provider table. useGoogleSearch works with Gemini only, and Seedream does not support 4K. For OpenAI permission errors, check your organization settings. For quota or rate-limit errors, check the selected provider account.
This repository also includes an Agent Skill for assistants that already have access to an image generation tool. It teaches the prompt-writing approach used by mcp-image and works independently of this server.
Install it with:
npx mcp-image skills install --path <skills-directory>
For example, use ~/.codex/skills, ~/.cursor/skills, or ~/.claude/skills as the destination.
MIT License. See LICENSE for details.
Need help? Open an issue or check Troubleshooting.