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)
Buy human image preference comparisons on the Pebbler app with locally controlled USDC payments.
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。
PEBBLER_ALLOW_PAYMENTS, PEBBLER_WALLET_PRIVATE_KEY, PEBBLER_MAX_PURCHASE_USDC, PEBBLER_MAX_TOTAL_USDC, PEBBLER_STATE_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": {
"pebbler": {
"command": "npx",
"args": [
"-y",
"@pebbler/pebbler-mcp"
],
"env": {
"PEBBLER_ALLOW_PAYMENTS": "your-value",
"PEBBLER_WALLET_PRIVATE_KEY": "your-value",
"PEBBLER_MAX_PURCHASE_USDC": "your-value",
"PEBBLER_MAX_TOTAL_USDC": "your-value",
"PEBBLER_STATE_DIR": "your-value"
}
}
}
}在终端中运行这条命令
claude mcp add pebbler --env PEBBLER_ALLOW_PAYMENTS=your-value --env PEBBLER_WALLET_PRIVATE_KEY=your-value --env PEBBLER_MAX_PURCHASE_USDC=your-value --env PEBBLER_MAX_TOTAL_USDC=your-value --env PEBBLER_STATE_DIR=your-value -- npx -y @pebbler/pebbler-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": {
"pebbler": {
"command": "npx",
"args": [
"-y",
"@pebbler/pebbler-mcp"
],
"env": {
"PEBBLER_ALLOW_PAYMENTS": "your-value",
"PEBBLER_WALLET_PRIVATE_KEY": "your-value",
"PEBBLER_MAX_PURCHASE_USDC": "your-value",
"PEBBLER_MAX_TOTAL_USDC": "your-value",
"PEBBLER_STATE_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": {
"pebbler": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@pebbler/pebbler-mcp"
],
"env": {
"PEBBLER_ALLOW_PAYMENTS": "your-value",
"PEBBLER_WALLET_PRIVATE_KEY": "your-value",
"PEBBLER_MAX_PURCHASE_USDC": "your-value",
"PEBBLER_MAX_TOTAL_USDC": "your-value",
"PEBBLER_STATE_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。
PEBBLER_ALLOW_PAYMENTS envPEBBLER_MAX_PURCHASE_USDC envPEBBLER_MAX_TOTAL_USDC envPEBBLER_STATE_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 bridge-applications 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:PEBBLER_WALLET_PRIVATE_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(0.1.0)于33天前进入注册中心。
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。
Let your agent collect human feedback on two images and explain the results. Pebbler runs image preference tests with participants on the Pebbler app.
Your agent retrieves current pricing, package details and availability before creating a test. The purchase uses a live quote and stays within the spending limits you configure. Pricing and package sizes are not fixed by this connector.
Version 1 supports image A/B preference tests. These measure which image people prefer, rather than product conversion or causal effects. Completed response counts are not guaranteed. Surveys and text-only comparisons are not supported.
Use an MCP app that supports local servers and Node.js 22 or later. Add this configuration to your app:
{
"mcpServers": { "pebbler": { "command": "npx", "args": ["-y", "@pebbler/pebbler-mcp@0.1.0"] } } }
Pebbler's production settings are included. You can explore current packages and create drafts without enabling payments.
Use a dedicated wallet funded with native USDC on Base. Configure these settings locally in your MCP app's environment or secret settings:
| Setting | What to provide |
|---|---|
PEBBLER_ALLOW_PAYMENTS | Set to true when you want the agent to make purchases |
PEBBLER_WALLET_PRIVATE_KEY | Your wallet's signing key, supplied privately |
PEBBLER_MAX_PURCHASE_USDC | Your chosen maximum spend per test, as a positive decimal USDC amount |
PEBBLER_MAX_TOTAL_USDC | Your chosen cumulative spending limit, as a positive decimal USDC amount |
Both spending limits are required when payments are enabled. They are your budget, not the price of a test. If a quote exceeds either limit, the connector stops instead of raising your budget. Payments stay disabled until you enable them explicitly.
The wallet key remains local. Do not put it in a prompt or share it in a conversation. Prices and quotes are fetched by the agent; you do not need to configure them.
For example:
Check the current package and price, then compare these two image URLs. Tell me the quote before buying and stay within my configured budget.
Provide two publicly accessible HTTPS image URLs and a clear question. Use images you own or have permission to use, and keep the URLs available while responses are collected.
Your agent can show the current offer, create a draft, purchase the test and check progress. You can read partial results while collection continues or return later to ask for the final counts and vote shares. Retrieving results is included in the purchase.
| Tool | Purpose |
|---|---|
get_catalog | Retrieve current packages, prices, supported inputs and availability |
create_study | Prepare an image comparison and obtain its quote |
quote_study | Refresh a quote before payment has been signed |
purchase_study | Purchase the quoted test within your wallet's spending limits |
get_study_status | Check progress and when to check again |
get_study_results | Retrieve aggregate A/B votes and shares |
list_local_studies | Find your saved tests after returning or restarting |
The agent learns each tool's inputs automatically when connected. It should read the catalog first, use the quote for the purchase, and follow the returned polling interval when checking progress.
Keep the connector's private local state folder backed up. It retains access to your tests and their purchase history across restarts. You can choose a folder with PEBBLER_STATE_DIR; use the same folder when returning to existing tests.
Your total spending limit counts retained signed purchases, including unresolved attempts, and does not reset automatically. Increase it deliberately if you want to buy more tests. Keep the original state rather than deleting it to reset your budget.
If a purchase is interrupted or pending, ask the agent to retry that same purchase. The connector preserves its identifiers and payment authorization instead of signing another payment. Reading progress and results does not require another purchase.
The included examples/run-study.mjs demonstrates discovery and creating an image comparison. It prints the live catalog and quote; purchasing requires the --purchase flag and your locally configured wallet and budgets.
MIT. Original example image assets are included under the same license.