Frontend Design Loop MCP
What it does
Design-first MCP for coding agents that improves websites with screenshot-grounded iteration.
- Connects 在你的电脑上运行
- Account or key No key needed
- Category 开发者工具
安装
选择你使用的 AI 应用,然后复制设置。
通过 3/3 项检查 · 在你的电脑上运行 · ✓ 命令已检查 2026年11月13日
第一步:你用哪个 AI?
选择你用的应用,步骤会显示在下方。
可连接 Claude,但需要先准备
需要先在电脑上安装 Python (uv)(只需一次) · 仅限电脑上的 Claude 应用(Windows 或 Mac),网页和手机不可用
打开电脑版 Claude 应用的设置文件
SettingsDeveloperEdit Config
粘贴这些设置并保存文件
{ "mcpServers": { "frontend-design-loop": { "command": "uvx", "args": [ "frontend-design-loop-mcp" ] } } }退出 Claude 再重新打开
试一试
用 Frontend Design Loop MCP 告诉我你能帮我做什么,然后做一件给我看✓ 如果 Claude 说正在使用 Frontend Design Loop MCP,或回答中出现 Frontend Design Loop MCP 的工具名称,就表示连接成功
菜单名称已于 2026年11月11日 对照 Anthropic 帮助页面核实 · 你的界面可能因版本略有不同
ChatGPT 暂时无法连接 Frontend Design Loop MCP
Frontend Design Loop MCP 需要安装在你的电脑上,而 ChatGPT 只能连接在网上运行的服务器
你可以改用这些方式
A · 使用能连接 Frontend Design Loop MCP 的应用
- 需要先在电脑上安装 Python (uv)(只需一次) · 仅限电脑上的 Claude 应用(Windows 或 Mac),网页和手机不可用
- 需要先在电脑上安装 Python (uv)(只需一次)
- 需要先在电脑上安装 Python (uv)(只需一次)
- 需要先在电脑上安装 Python (uv)(只需一次)
B · 开发者工具 类中能连接 ChatGPT 的其他服务器
从同类中使用较多的里挑选,仅限用地址即可连接、无需密钥的
- Sentry✓ ChatGPT
- Compiler Explorer✓ ChatGPT
- GitDiagram✓ ChatGPT
可连接 Claude Code,但需要先准备
需要先在电脑上安装 Python (uv)(只需一次)
打开终端
Mac:按 Command+空格,输入 Terminal · Windows:打开 PowerShell
粘贴这条命令并按 Enter
claude mcp add --scope user frontend-design-loop -- uvx frontend-design-loop-mcp在 Claude Code 中输入 /mcp
应能看到 Frontend Design Loop MCP 在列表中并显示已连接
试一试
用 Frontend Design Loop MCP 告诉我你能帮我做什么,然后做一件给我看✓ 如果 Claude Code 说正在使用 Frontend Design Loop MCP,或回答中出现 Frontend Design Loop MCP 的工具名称,就表示连接成功
菜单名称已于 2026年11月11日 对照 Anthropic 帮助页面核实 · 你的界面可能因版本略有不同
可连接 Cursor,但需要先准备
需要先在电脑上安装 Python (uv)(只需一次)
在 Cursor 中以 Agent 模式打开 AI 聊天
试一试
用 Frontend Design Loop MCP 告诉我你能帮我做什么,然后做一件给我看✓ 如果 Cursor 说正在使用 Frontend Design Loop MCP,或回答中出现 Frontend Design Loop MCP 的工具名称,就表示连接成功
菜单名称已于 2026年11月11日 对照 Cursor 帮助页面核实 · 你的界面可能因版本略有不同
可连接 VS Code,但需要先准备
需要先在电脑上安装 Python (uv)(只需一次)
在 VS Code 中以 Agent 模式打开 AI 聊天
试一试
用 Frontend Design Loop MCP 告诉我你能帮我做什么,然后做一件给我看✓ 如果 VS Code 说正在使用 Frontend Design Loop MCP,或回答中出现 Frontend Design Loop MCP 的工具名称,就表示连接成功
菜单名称已于 2026年11月11日 对照 VS Code 帮助页面核实 · 你的界面可能因版本略有不同
开发者专用:终端命令和 JSON 设置
安装在电脑上
Claude Code
claude mcp add --scope user frontend-design-loop -- uvx frontend-design-loop-mcpClaude Desktop (claude_desktop_config.json)
{
"mcpServers": {
"frontend-design-loop": {
"command": "uvx",
"args": [
"frontend-design-loop-mcp"
]
}
}
}Cursor (~/.cursor/mcp.json)
{
"mcpServers": {
"frontend-design-loop": {
"command": "uvx",
"args": [
"frontend-design-loop-mcp"
]
}
}
}VS Code (mcp.json)
{
"servers": {
"frontend-design-loop": {
"type": "stdio",
"command": "uvx",
"args": [
"frontend-design-loop-mcp"
]
}
}
}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。
一览
哪些应用可以使用它
依据这个服务器的连接方式和各应用自己的文档,检查于 2026年11月10日。
在你的电脑上运行,适用于
ClaudeGooseLM StudioMsty StudioCherry StudioCursorVS Code + GitHub CopilotVisual StudioWindsurf (Devin Desktop)ZedKiroClineContinueJetBrains AI AssistantClaude CodeCodex CLIGemini CLIOpenCodenodecodeWarpLibreChatRaycast
它能做什么
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。
基础检查i
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13日
- ✓ 通过
作者与仓库一致
注册名称已通过 GitHub 账户 alexalexalex222 验证,该账户拥有此仓库
- ✓ 通过
仍在维护
代码最后更新于38天前
- ✓ 通过
有许可证
使用 MIT
- – 不适用
端点有响应
它在你的电脑上运行,没有互联网端点
- – 不适用
使用 OAuth 登录
在你的电脑上运行,改用本地设置
- … 尚未检查
工具描述中没有隐藏指令
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
讨论
提问、分享技巧或报告无法使用。按“有帮助”数量排序。
用户评价
还没有评价
与“开发者工具”中的其他服务器比较i
- 星标数多于此分类中其他 5828 个服务器的 77%
- 发布到注册中心的时间比此分类中其他 5828 个服务器的 5% 更新
- 基础检查结果等于或优于此分类中其他 5828 个服务器的 100%
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。
常见问题
Frontend Design Loop MCP 安全吗?
它在 3 项适用的基础检查中通过了 3 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。
它需要哪些密钥或代码?
注册中心没有列出必需的密钥,不过有些服务器会在首次使用时要求你登录。
它在我的电脑上运行还是在云端?
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)。
它还在维护吗?
GitHub 仓库最后更新于38天前,最新版本(1.0.0)于8个月前进入注册中心。
哪些应用可以使用它?
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 Python (uv)。
有什么可以替代它?
同一分类中有:REA, GitHub, Serena MCP: the IDE for your agent
同类别的其他选择
同一分类中其他作者的服务器,按星标数排序。
如何看卡片:↓ 每周下载量i★ 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
GitHub
Connect AI assistants to GitHub - manage repos, issues, PRs, and workflows through natural language.
Serena MCP: the IDE for your agent
A powerful toolkit for coding, providing semantic retrieval and editing capabilities.
作者的 README
打开 README
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。
Frontend Design Loop MCP
Coding agents can get a page functional. Frontend Design Loop makes it materially better with screenshot-grounded iteration and proof artifacts.
Use it when the base model got the page working but the result is still generic, flat, rough, or visibly under-designed. The main design workflow stays on one main provider and model lane by default, so multi-model routing is opt-in instead of the default story.
Quick Start
Install the current public build from PyPI:
pipx install frontend-design-loop-mcp
Set up every detected supported client:
frontend-design-loop-setup --install-all-detected-clients
Real MCP call example:
frontend_design_loop_design(
repo_path="/absolute/path/to/site", goal="make the homepage look materially more premium without changing the information architecture", provider="gemini_cli", model="gemini-3.1-pro-preview", preview_command="python3 -m http.server {port}", preview_url="http://127.0.0.1:{port}/index.html" )
Agent-Owned Toolkit Variant
This repo now also ships an additive MCP entrypoint for agent-owned frontend loops:
- console script:
frontend-design-toolkit-mcp - module fallback:
PYTHONPATH=src .venv/bin/python -m design_toolkit.server
That variant is intentionally narrow:
get_playbookbuild_contextrun_gatespreview_startcapture_screenshotspreview_stop
It does not hide vision scoring, creativity judging, or patch generation behind MCP. The host agent owns planning, edits, screenshot review, scoring, iteration, and winner selection directly.
See test-prompt-codex.md for the end-to-end Codex exercise prompt.
What The MCP Does
frontend_design_loop_design is the main workflow:
- the host agent points the MCP at a real repo plus a concrete design goal
- the MCP boots a local preview, captures screenshots, and iterates against the rendered result
- the same main provider and model lane is used by default across planning, generation, and vision unless you explicitly override it
- the MCP returns the winning patch plus screenshots and run artifacts
frontend_design_loop_eval is the proof workflow:
- use it when the host agent already has the patch
- the MCP applies the patch in an isolated worktree, runs deterministic checks, captures screenshots, and returns proof artifacts
This is the wedge:
- coding agents can already get pages working
- this MCP helps them make pages materially better
- screenshot-grounded iteration plus proof artifacts is the differentiator
Official MCP Registry metadata is tracked in server.json.
Proof Gallery
The public proof set uses owned/generated GA SMB previews plus the ACA full-page before/after.
Selected Hero / Top Crops
11 Budget Movers Augusta
13 Peachtree Flooring Atlanta
19 TNT Cabinets Columbus
21 Henry Plumbing Savannah
22 Silverback Electric Savannah
25 Robins Body & Paint Warner Robins
34 Proof Roofing Services Gainesville
45 Metro Storage Columbus
47 Miller Light Construction Commerce
ACA Full-Page Before / After
Before: early ACA full homepage.
After: rebuilt ACA homepage with a stronger hero, cleaner sequencing, and a materially better full-page result.
See the proof notes in the case studies index.
How It Works In Practice
- Point the MCP at a real repo and give it a concrete design goal.
- It creates an isolated worktree, boots a preview, and captures rendered screenshots.
- It iterates against the actual rendered page instead of only raw code.
- It returns the winning patch, screenshot proof, and run artifacts so the host agent can judge the result.
Workflow Summary
frontend_design_loop_design
Use it when:
- the page is functional but weak
- the section structure is there but the design is not
- you want the MCP to improve the page instead of only judging it
Key defaults:
- one main
provider+modellane by default planning_mode="single"vision_mode="on"section_creativity_mode="on"- split planner or vision lanes only happen when explicitly requested
frontend_design_loop_eval
Use it when:
- the host agent already has the patch
- you want deterministic checks, screenshots, and artifact capture
- you want the host agent to judge the result from returned screenshots
Returned proof fields include:
deterministic_passedvision_pendingvision_scoredfinal_passrun_dircandidate_dirscreenshot_filespatch
frontend_design_loop_solve
frontend_design_loop_solve still exists for advanced unattended workflows, but it is not the main public story.
Install And Setup
Public install now
pipx install frontend-design-loop-mcp
frontend-design-loop-setup --install-all-detected-clients
GitHub install remains the fallback:
pipx install git+https://github.com/alexalexalex222/frontend-design-loop-mcp.git
frontend-design-loop-setup --install-all-detected-clients
Local clone path
git clone https://github.com/alexalexalex222/frontend-design-loop-mcp.git
cd frontend-design-loop-mcp ./scripts/setup.sh
The local setup path:
- creates
.venv - installs the package
- installs Playwright Chromium
- installs detected client entries when supported clients are present
- runs the built-in doctor
- runs the stdio smoke test
If you want the repo-local environment without auto-installing client entries:
FDL_SKIP_CLIENT_INSTALL=1 ./scripts/setup.sh
Setup helpers
Bulk installer:
frontend-design-loop-setup --install-all-detected-clients
Targeted installers:
frontend-design-loop-setup --install-claude --scope user
frontend-design-loop-setup --install-codex frontend-design-loop-setup --install-gemini frontend-design-loop-setup --install-droid frontend-design-loop-setup --install-opencode
Config printers:
frontend-design-loop-setup --print-claude-config
frontend-design-loop-setup --print-codex-config frontend-design-loop-setup --print-gemini-config frontend-design-loop-setup --print-droid-config frontend-design-loop-setup --print-opencode-config
Safety Defaults
- custom commands are parsed as shell-free argv by default
- shell syntax, substitutions, and inline interpreter execution like
bash -c,python -c, andnode -erequireunsafe_shell_commands=true preview_urlmust match the launched local preview origin and port by default- external preview fetches require
unsafe_external_preview=true - preview readiness checks reject cross-origin redirects, and browser screenshots block cross-origin subresources by default
- auto-context skips common secret-bearing paths such as
.env*,.git/,.aws/,.ssh/,.config/gcloud/,.docker/,.kube/, token-named files, and service-account-style JSON - native CLI providers inherit a minimal allowlisted environment instead of the full host shell environment
- shared worktree reuse directories are off by default
Client-side vision is the default proof path for frontend_design_loop_eval, so the host agent can judge the screenshots without provider credentials.
Proxy-only MiniMax vision lanes are explicitly treated as structural-only review:
vision_review_mode="proxy_structural"- they do not count as full automated visual scoring
Verification
Offline preflight:
PYTHONPATH=src .venv/bin/python scripts/preflight_check.py
stdio smoke:
PYTHONPATH=src .venv/bin/python scripts/smoke_mcp_stdio.py
Built-in doctor:
frontend-design-loop-setup --doctor
frontend-design-loop-setup --doctor --smoke
Docs
Distribution State
Current public install path:
pipx install frontend-design-loop-mcp