The output

Give it a URL; get a report of bugs — each tagged with whether Argus independently reproduced it or only observed it:

The green badge is the whole point. Anyone can have an LLM claim a bug. Argus re-loads the page from scratch and re-checks the symptom before it says VERIFIED — so the report is a list of bugs you can trust, not a list of guesses to triage.

How it works

flowchart LR
    A(["observe"]) --> B{"looks wrong?"}
    B -->|not sure| C["act: click · type · resize · verify"]
    C --> A
    B -->|bug| D["verify_persistence — reload from a clean state"]
    D -->|symptom repeats| E(["VERIFIED"])
    D -->|symptom gone| F(["dropped — no false positive"])
    E --> G[["report: HTML · JSON · JUnit · SARIF"]]

The agent is the intelligence. Argus supplies concise QA guidance, a description-keyed tool surface (click_what("Login button"), not click(7)), and a reproduction-receipt engine that turns "the model thinks this is a bug" into "this bug is real, here's the proof."

Quick start

pip install argus-testing
playwright install chromium

# Wire it into Claude Code (or Cursor, or any MCP host)
claude mcp add argus -- argus-mcp

The default core profile exposes the primary web-testing workflow without flooding the host with every specialist tool. Use argus-mcp --list-tools to inspect the selected profile, --tool-profile screen for native macOS testing, or --tool-profile full for the entire advanced surface. ARGUS_TOOL_PROFILE provides the same setting through the environment.

Then just ask, in your agent session:

"Test my app at http://localhost:3000 — find real bugs."

That's it. The agent drives; Argus keeps it honest and writes the report.

# Uses a LiteLLM-backed planner. Set a provider key (OPENAI_API_KEY, DEEPSEEK_API_KEY, …).
argus http://localhost:3000 --model deepseek/deepseek-chat

# Higher recall: union N independent passes (deduped, proven instance kept)
argus http://localhost:3000 --passes 3

pip install 'argus-testing[mac]'
brew install cliclick          # keystroke / coordinate fallback
argus-mcp --doctor             # check Screen Recording + Accessibility grants
claude mcp add argus-screen -- argus-mcp --tool-profile screen

Why Argus is different

Existing testing tools only test what you script. Playwright and Cypress run the assertions you wrote. Argus discovers bugs you didn't think to test for — and then does the thing an LLM alone can't be trusted to do: proves them.

How it compares

On the axis that matters for finding bugs — autonomously discover, independently verify, and report — Argus occupies a different slot from the browser-MCP crowd:

These aren't "worse" tools — they're a different job. Playwright MCP gives an agent excellent hands; Chrome DevTools MCP gives it deep network/perf/memory inspection Argus doesn't have. Argus is the layer that decides what's a bug and proves it. Use them together.

Benchmarks

$ python -m argus.bench --target all

  buggytasks    22 / 22  = 100 %   ·  mechanical bugs (console errors, fake delete, auth bypass…)
  darkshop      12 / 12  = 100 %   ·  human-eye bugs (fake scarcity, lying toasts, stale state…)
  ──────────────────────────────────────────────────────────────────────
  total         34 / 34  = 100 %   ·  reproducible from git clone in two commands

34 / 34 is the capability ceiling — what's findable through the tool surface, measured by deterministic scripts. It is deliberately separate from how often a given LLM remembers to use the tools well, which is noisy and honestly reported below.

python test-site/app.py           # BuggyTasks  :5555
python human-eye-fixture/app.py   # DarkShop    :5556
python -m argus.bench --target all

Tool surface

argus-mcp starts with the focused core web profile. The tables below describe the wider surface; start with --tool-profile full only when you need specialist network, storage, tab, coordinate, or crawl controls. Screen mode has its own focused profile.

Reports keep original screenshots as evidence and, by default, write compact WebP previews under report-assets/ instead of base64-embedding every full-size PNG into the HTML. Set ARGUS_PORTABLE_REPORT=1 when a single self-contained HTML file is more important than size. JSON output includes complete reproduction receipts, review mode, tool-call and recorded-step counts, screenshot metadata, and qualitative observations. JUnit suite failure totals match the emitted <failure> nodes.

Philosophy

Project layout

argus/
├── mcp_server.py     # tool surface + role instructions + reproduction-receipt engine
├── browser.py        # Playwright backend: DOM/ARIA extraction, capsule/replay
├── resolver.py       # description → element (web + screen)
├── reporter.py       # HTML + JSON + JUnit + SARIF
├── detector.py       # console + network capture (only)
├── cli.py            # argus (explore) + argus-regression
├── bench/            # deterministic ceiling + real-LLM recall harness
└── screen/           # macOS AX backend, permissions, safety
test-site/            # BuggyTasks  (22 mechanical bugs)
human-eye-fixture/    # DarkShop    (12 human-eye bugs)