Figma Context MCP
Give your coding agent access to your Figma data. Implement designs in any framework in one-shot.
作者提供的说明(英文原文)
AI image generation and editing with prompt optimization and quality presets
这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。
我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。
选择你使用的 AI 应用,然后复制设置。
IMAGE_PROVIDER, GEMINI_API_KEY, OPENAI_API_KEY, ARK_API_KEY, IMAGE_OUTPUT_DIR, IMAGE_QUALITY, SKIP_PROMPT_ENHANCEMENT标为机密的值是你账户的钥匙。千万不要分享给别人,也不要粘贴到聊天里。
你需要
你用的是哪个应用?
在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。
打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 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"
}
}
}
}在终端中运行这条命令
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-image运行前请先填写空着的值。
粘贴到项目中的 .cursor/mcp.json,或 ~/.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"
}
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
粘贴到项目中的 .vscode/mcp.json
{
"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"
}
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
这个服务器在你的电脑上运行,而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。
你的选择通过 Cookie 保存在这台设备上,无需账户。
IMAGE_PROVIDER envIMAGE_OUTPUT_DIR envIMAGE_QUALITY envSKIP_PROMPT_ENHANCEMENT env这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。
它在你的电脑上运行;安装后,工具列表会显示在你的 AI 应用中。
我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月7日
注册名称已通过 GitHub 账户 shinpr 验证,该账户拥有此仓库
我们还没有从 GitHub 读取这个仓库
我们还没有从 GitHub 读取这个仓库
它在你的电脑上运行,没有互联网端点
在你的电脑上运行,改用本地设置
它在你的电脑上运行;我们只能读取互联网端点的工具列表
与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。
它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。
你需要填写:GEMINI_API_KEY, OPENAI_API_KEY, ARK_API_KEY
它在你的电脑上运行。你的 AI 应用会在需要时启动它,数据不会经过作者的服务器(除非它自己调用在线服务)。
GitHub 仓库最后更新于–,最新版本(0.19.0)于前天进入注册中心。
支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 Node.js。
同一分类中有:Figma Context MCP, Claude Real Video, Figma MCP Server
同一分类中其他作者的服务器,按星标数排序。
如何看卡片:★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间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.
按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。
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.