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)
Gemini 3 MCP server with 30+ tools: images, video, research, TTS, code exec & CLI
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。
GEMINI_API_KEY, GEMINI_OUTPUT_DIR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": {
"gemini": {
"command": "npx",
"args": [
"-y",
"@rlabs-inc/gemini-mcp"
],
"env": {
"GEMINI_API_KEY": "your-value",
"GEMINI_OUTPUT_DIR": "your-value"
}
}
}
}在终端中运行这条命令
claude mcp add gemini --env GEMINI_API_KEY=your-value --env GEMINI_OUTPUT_DIR=your-value -- npx -y @rlabs-inc/gemini-mcp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": {
"gemini": {
"command": "npx",
"args": [
"-y",
"@rlabs-inc/gemini-mcp"
],
"env": {
"GEMINI_API_KEY": "your-value",
"GEMINI_OUTPUT_DIR": "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": {
"gemini": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@rlabs-inc/gemini-mcp"
],
"env": {
"GEMINI_API_KEY": "your-value",
"GEMINI_OUTPUT_DIR": "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。
GEMINI_OUTPUT_DIR 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 RLabs-Inc 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
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(0.7.1)于10个月前进入注册中心。
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。
A Model Context Protocol (MCP) server for integrating Google's Gemini 3 models with Claude Code, enabling powerful collaboration between both AI systems. Now with a beautiful CLI!
MCP Registry Support: Now discoverable in the official MCP ecosystem!
| Feature | Description |
|---|---|
| Deep Research Agent | Autonomous multi-step research with web search and citations |
| Token Counting | Count tokens and estimate costs before API calls |
| Text-to-Speech | 30 unique voices, single speaker or two-speaker dialogues |
| URL Analysis | Analyze, compare, and extract data from web pages |
| Context Caching | Cache large documents for efficient repeated queries |
| YouTube Analysis | Analyze videos by URL with timestamp clipping |
| Document Analysis | PDFs, DOCX, spreadsheets with table extraction |
| 4K Image Generation | Generate images up to 4K with 10 aspect ratios |
| Multi-Turn Image Editing | Iteratively refine images through conversation |
| Video Generation | Create videos with Veo 2.0 (async with polling) |
| Code Execution | Gemini writes and runs Python code (pandas, numpy, matplotlib) |
| Google Search | Real-time web information with inline citations |
| Structured Output | JSON responses with schema validation |
| Data Extraction | Extract entities, facts, sentiment from text |
| Thinking Levels | Control reasoning depth (minimal/low/medium/high) |
| Direct Query | Send prompts to Gemini 3 Pro/Flash models |
| Brainstorming | Claude + Gemini collaborative problem-solving |
| Code Analysis | Analyze code for quality, security, performance |
| Summarization | Summarize content at different detail levels |
# Using npm (Recommended)
claude mcp add gemini -s user -- env GEMINI_API_KEY=YOUR_KEY npx -y @rlabs-inc/gemini-mcp
claude mcp add gemini -s user -- env GEMINI_API_KEY=YOUR_KEY bunx @rlabs-inc/gemini-mcp
# Install globally
npm install -g @rlabs-inc/gemini-mcp
gcli config set api-key YOUR_KEY
gcli search "latest news" glci image "sunset over mountains" --ratio 16:9
Get your API key: Visit Google AI Studio - it's free and takes seconds!
# With verbose logging
claude mcp add gemini -s user -- env GEMINI_API_KEY=YOUR_KEY VERBOSE=true bunx -y @rlabs-inc/gemini-mcp
claude mcp add gemini -s user -- env GEMINI_API_KEY=YOUR_KEY GEMINI_OUTPUT_DIR=/path/to/output bunx -y @rlabs-inc/gemini-mcp
Direct queries to Gemini with thinking level control:
prompt: "Explain quantum entanglement"
model: "pro" or "flash" thinkingLevel: "low" | "medium" | "high" (optional)
Generate images with Nano Banana Pro (Claude can SEE them!):
prompt: "a futuristic city at sunset"
style: "cyberpunk" (optional) aspectRatio: "16:9" (1:1, 2:3, 3:2, 3:4, 4:3, 4:5, 5:4, 9:16, 16:9, 21:9) imageSize: "2K" (1K, 2K, 4K) useGoogleSearch: false (ground in real-world info) thinkingLevel: "high" (optional - minimal, low, medium, high) personGeneration: "ALLOW_ALL" (optional - ALLOW_ALL, ALLOW_ADULT, ALLOW_NONE) seed: 42 (optional - for reproducible results)
Start a multi-turn image editing session:
prompt: "a cozy cabin in the mountains"
aspectRatio: "16:9" imageSize: "2K" useGoogleSearch: false thinkingLevel: "high" (optional - minimal, low, medium, high) personGeneration: "ALLOW_ALL" (optional - ALLOW_ALL, ALLOW_ADULT, ALLOW_NONE) seed: 42 (optional - for reproducible results)
Returns a session ID for iterative editing.
Continue refining an image:
sessionId: "edit-123456789"
prompt: "add snow on the roof and make it nighttime"
Close an editing session:
sessionId: "edit-123456789"
List all active editing sessions.
Generate videos using Veo:
prompt: "a cat playing piano"
aspectRatio: "16:9" (optional) negativePrompt: "blurry, text" (optional)
Video generation is async (takes 1-5 minutes). Use gemini-check-video to poll.
Check video generation status and download when complete:
operationId: "operations/xxx-xxx-xxx"
Analyze code for issues:
code: "function foo() { ... }"
language: "typescript" (optional) focus: "quality" | "security" | "performance" | "bugs" | "general"
Analyze text content:
text: "Your text here..."
type: "sentiment" | "summary" | "entities" | "key-points" | "general"
Collaborative brainstorming:
prompt: "How could we implement real-time collaboration?"
claudeThoughts: "I think we should use WebSockets..." maxRounds: 3 (optional)
Summarize content:
content: "Long text to summarize..."
length: "brief" | "moderate" | "detailed" format: "paragraph" | "bullet-points" | "outline"
Let Gemini write and execute Python code:
prompt: "Calculate the first 50 prime numbers and plot them"
data: "optional CSV data to analyze" (optional)
Supports libraries: numpy, pandas, matplotlib, scipy, scikit-learn, tensorflow, and more. Generated charts are saved to the output directory and returned as images.
Real-time web search with citations:
query: "What happened in tech news this week?"
returnCitations: true (default)
Returns grounded responses with inline citations and source URLs.
Get JSON responses matching a schema:
prompt: "Extract the meeting details from this email..."
schema: '{"type":"object","properties":{"date":{"type":"string"},"attendees":{"type":"array"}}}' useGoogleSearch: false (optional)
Convenience tool for common extraction patterns:
text: "Your text to analyze..."
extractType: "entities" | "facts" | "summary" | "keywords" | "sentiment" | "custom" customFields: "name, date, amount" (for custom extraction)
Analyze YouTube videos directly:
url: "https://www.youtube.com/watch?v=..."
question: "What happens at 2:30?" startTime: "1m30s" (optional, for clipping) endTime: "5m00s" (optional, for clipping)
Quick video summarization:
url: "https://www.youtube.com/watch?v=..."
style: "brief" | "detailed" | "bullet-points" | "chapters"
Analyze PDFs and documents:
filePath: "/path/to/document.pdf"
question: "Summarize the key findings" mediaResolution: "low" | "medium" | "high"
Quick PDF summarization:
filePath: "/path/to/document.pdf"
style: "brief" | "detailed" | "outline" | "key-points"
Extract tables from documents:
filePath: "/path/to/document.pdf"
outputFormat: "markdown" | "csv" | "json"
The killer combination for development:
| Claude | Gemini |
|---|---|
| Complex logic | Frontend/UI |
| Architecture | Visual components |
| Backend code | Image generation |
| Integration | React/CSS styling |
| Reasoning | Creative generation |
Example workflow:
gemini-generate-image for UI mockupsgemini-query| Variable | Required | Default | Description |
|---|---|---|---|
GEMINI_API_KEY | Yes | - | Your Google Gemini API key |
GEMINI_OUTPUT_DIR | No | ./gemini-output | Where to save generated files |
GEMINI_MODEL | No | - | Override model for init test |
GEMINI_PRO_MODEL | No | gemini-3-pro-preview | Pro model (Gemini 3) |
GEMINI_FLASH_MODEL | No | gemini-3-flash-preview | Flash model (Gemini 3) |
GEMINI_IMAGE_MODEL | No | gemini-3-pro-image-preview | Image model (Nano Banana Pro) |
GEMINI_IMAGE_THINKING_LEVEL | No | high | Default thinking level for image generation (minimal, low, medium, high) |
GEMINI_VIDEO_MODEL | No | veo-2.0-generate-001 | Video model |
VERBOSE | No | false | Enable verbose logging |
QUIET | No | false | Minimize logging |
GEMINI_ENABLED_TOOLS | No | - | Comma-separated list of tool groups to load (e.g., query,search,image-gen) |
GEMINI_TOOL_PRESET | No | - | Preset profile: minimal, text, image, research, media, full |
By default, all 37 tools are loaded. To reduce context usage, configure which tools to load:
| Preset | Tool Groups |
|---|---|
minimal | query, brainstorm |
text | query, brainstorm, analyze, summarize, structured |
image | query, image-gen, image-edit, image-analyze |
research | query, search, deep-research, url-context, document |
media | query, image-gen, image-edit, image-analyze, video-gen, youtube, speech |
full | All 18 tool groups (default) |
# Minimal - query and brainstorm
GEMINI_TOOL_PRESET=minimal
GEMINI_TOOL_PRESET=text # query, brainstorm, analyze, summarize, structured
GEMINI_TOOL_PRESET=image # query, image-gen, image-edit, image-analyze
GEMINI_TOOL_PRESET=research # query, search, deep-research, url-context, document
# Only specific tools
GEMINI_ENABLED_TOOLS=query,search,image-gen
# Start with preset, add extras
GEMINI_TOOL_PRESET=minimal GEMINI_ENABLED_TOOLS=search,image-gen # Adds to minimal preset
| Group | Tools |
|---|---|
query | gemini-query |
brainstorm | gemini-brainstorm |
analyze | gemini-analyze-code, gemini-analyze-text |
summarize | gemini-summarize |
image-gen | gemini-generate-image, gemini-image-prompt |
| image-edit | gemini-start-image-edit, gemini-continue-image-edit, gemini-end-image
只显示了开头部分;其余内容请在仓库中阅读