fagun 0.2.0

Fagun — one MCP server that lets any AI tool (Claude, Cursor, Codex, Antigravity, Windsurf) drive a browser, hunt bugs, and run a full QA sweep.

🦊 Fagun

One MCP server. Every AI tool. Type fagun and it drives a browser + runs full QA.

Fagun is an MCP server that lets any AI coding tool — Claude Code / Desktop, Cursor, Codex, Antigravity, Windsurf, Cline, VS Code — control a real browser, debug it (console, network, DOM, screenshots, JS eval), and run an automated quality sweep (broken requests, console errors, accessibility, performance, SEO) with a Markdown report.

You set it up once. Then inside any of those tools you just say fagun (or /fagun) and it starts.

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One-line setup (paste into your AI tool)

Tell your AI agent (Claude, Cursor, Codex, Antigravity, …) exactly this:

Install or upgrade fagun to the latest stable version with uv using Python 3.12, register the skill from fagun skill, and connect it to my browser. Follow https://github.com/mejbaurbahar/fagun/blob/main/install.md if setup or connection fails.

The agent follows install.md and wires everything up. Then just type /fagun and describe what to test.

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Setup (once, ~2 min)

1. Install the runner + browser engine

pip install uv
uvx --from fagun python -m playwright install chromium

uvx runs Fagun without a permanent install and always uses the latest version.

2. Add Fagun to your AI tool

Print ready-to-paste config for every tool:

uvx fagun install

Or let Fagun write the file for you:

uvx fagun install cursor     # writes ~/.cursor/mcp.json
uvx fagun install claude     # writes Claude Desktop config
uvx fagun install vscode     # writes .vscode/mcp.json

Manual config is identical everywhere — command uvx, args ["fagun"]:

Tool	Where
Claude Code	claude mcp add fagun -- uvx fagun
Claude Desktop	~/Library/Application Support/Claude/claude_desktop_config.json
Cursor	~/.cursor/mcp.json
Windsurf / Cline / Antigravity	their MCP settings (same JSON as Cursor)
VS Code (Copilot)	.vscode/mcp.json
Codex CLI	~/.codex/config.toml

// Claude Desktop / Cursor / Windsurf / Cline / Antigravity
{ "mcpServers": { "fagun": { "command": "uvx", "args": ["fagun"] } } }

# Codex ~/.codex/config.toml
[mcp_servers.fagun]
command = "uvx"
args = ["fagun"]

3. Restart the tool. Say fagun.

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Use it

Inside any tool, just talk:

• "fagun" → shows the menu and starts up

• "go to example.com and screenshot it"

• "run QA on https://example.com"

• "full QA sweep of https://example.com, write the report to ./qa.md"

• "show me the console errors" · "any failed network requests?"

• "click Sign in, type [e-mail] into email, press Enter"

• "deep test https://example.com and write the report to ./report.md" — the full sweep

The /fagun skill — autonomous bug hunter

skills/fagun/SKILL.md is a full QA methodology the AI follows: it hunts real, reproducible bugs across 10 scenario classes — functional, JS/runtime errors, network/API, form validation, auth/session/authorization, accessibility, performance, visual/responsive, security posture, and edge cases — with an evidence-or-it-didn't-happen rule and impact-based severity. Register it (see install.md Step 5) to get the /fagun slash command.

What it exposes (MCP tools)

fagun_start · open_browser · navigate · click · fill · press_key · screenshot · evaluate_js · get_console · get_network · crawl · run_qa · check_links · test_forms · security_headers · deep_test · full_qa_sweep · write_report · close_browser

Plus a fagun prompt — appears as a slash command in tools that surface MCP prompts.

Options (env vars)

Var	Default	Meaning
FAGUN_HEADLESS	1	0 shows the browser window
FAGUN_BROWSER	chromium	chromium | firefox | webkit
FAGUN_CDP_URL	—	Attach to a running Chrome, e.g. http://127.0.0.1:9222

Local dev

git clone <repo> && cd fagun
pip install -e .
python -m playwright install chromium
python -m fagun        # starts the MCP server on stdio

Releasing to PyPI (maintainer)

Auto-publish is wired via GitHub Actions using PyPI Trusted Publishing (OIDC — no API token stored). One-time setup on pypi.org:

• Project: fagun · Owner: mejbaurbahar · Repo: fagun
• Workflow: publish.yml · Environment: pypi

Then every release is just a tag:

# bump version in pyproject.toml + src/fagun/__init__.py first
git tag v0.2.0 && git push origin v0.2.0

The Publish to PyPI workflow builds, checks, and uploads automatically. Build locally to verify anytime: python -m build && twine check dist/*.

MIT © Mejbaur Bahar Fagun