argus
An agentic QA framework that authors, generates, triages, and self-heals Playwright tests for any web app, usable from Claude Code/Desktop as an MCP server or from CI as a CLI.
README
ποΈ Argus β Agentic QA Framework
An agentic QA framework that authors, generates, triages, and self-heals Playwright tests for any web app β usable from Claude Code/Desktop as an MCP server or from CI as a CLI β with the whole loop running as a deployment gate in GitHub Actions.
[!NOTE] π§ Early development. Build progress is tracked as milestones M0 β M4 (see Roadmap).
Why
Test suites are expensive to write and brittle to maintain. Argus puts a Claude agent in the loop to do the slow parts: explore an app and write real Playwright tests, then β when the UI drifts β diagnose the failure and open a fix PR, while still refusing to paper over genuine bugs.
The idea: one core, two consumers
Argus defines its QA tools once and exposes them twice.
ββββββββββββββββββββββββββββββββ
β @argus/core β
β Agent loop (Claude) β Anthropic Messages API + tool use
β + single Tool Registry β browser Β· dom Β· fs Β· playwright Β· git
βββββββββ¬ββββββββββββββββ¬βββββββ
β β
ββββββββββββββββΌβββ ββββΌββββββββββββββββ
β @argus/mcp β β @argus/cli β
β MCP server β β npx argus ... β
β (Claude Desktop)β β (used in CI) β
βββββββββββββββββββ ββββββββββββββββββββ
The loop: four behaviors
| Stage | Input | The agent⦠| Output |
|---|---|---|---|
| Author | Plain-English intent | compiles intent into a structured test plan | *.plan.json |
| Generate | A URL | explores the app, writes specs with assertions | tests/*.spec.ts |
| Triage | A failed run | classifies real bug vs DOM drift vs flake | root-cause report |
| Heal | A drift verdict | rewrites the locator, verifies green, opens a PR | a pull request |
Quickstart
pnpm install
cp .env.example .env # add your ANTHROPIC_API_KEY
pnpm build
Watch the agent run (E2E)
The agent loop is live. Point it at the bundled demo app and watch it explore β navigate, snapshot
the DOM, read data-testids, and click through the login β cart flow:
pnpm --filter @argus/core exec playwright install chromium # one-time
pnpm --filter @argus/sample-shop dev # terminal 1 β http://localhost:3100
node --env-file=.env packages/cli/dist/index.js smoke http://localhost:3100/login # terminal 2
It prints a step-by-step trace and a token/cost line (~$0.05β0.15 per run on the fast model). Requires a real Anthropic API key (a Max subscription doesn't fund the API).
Or have it write a test and run it green:
node --env-file=.env packages/cli/dist/index.js generate http://localhost:3100/login --run
It explores the app, writes tests/generated/login.spec.ts, and runs it against sample-shop
(3 passed, 0 failed). Defaults to Opus for quality; add --model claude-haiku-4-5 for ~10Β’ runs.
Full CLI / MCP usage docs land with milestones M2 and M4.
Repo layout
argus/
ββ packages/
β ββ core/ # agent loop, tool registry, Claude client, prompts
β ββ mcp/ # MCP server wrapping the registry
β ββ cli/ # `argus author|generate|triage|heal`
ββ apps/
β ββ sample-shop/ # Next.js demo target (login + products + cart)
ββ tests/ # generated Playwright specs land here
Roadmap
- M0 β Foundations Β· monorepo, tooling, CI stub
- M1 β Core + sample-shop + Generate Β· the first "AI writes real tests" moment
- M2 β CLI + GitHub Actions gate Β· failing tests block deployment
- M3 β Triage + Heal Β· self-healing PRs
- M4 β MCP server + polish Β· drive Argus from Claude Desktop; demo GIFs
License
MIT Β© Piyush Pathak
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.