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"
)

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.

Whole-Page Proof

The public proof set only uses owned/generated assets.

Before: early ACA full homepage.

ACA full-page before

After: rebuilt ACA homepage with a stronger hero, cleaner sequencing, and a materially better full-page result.

ACA full-page after

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 + model lane 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_passed
vision_pending
vision_scored
final_pass
run_dir
candidate_dir
screenshot_files
patch

`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, and node -e require unsafe_shell_commands=true
preview_url must 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

MCP Servers