
Cowork Qa MCP
- Updated May 6, 2026
- inSideos-designs/cowork-qa-mcp
Cowork QA is an MCP server that runs goal-driven Playwright browser sessions for LLMs with full action traces and aria-snapshots.
About
Cowork QA is an MCP server that lets coding agents execute structured Playwright browser work against a stated goal, returning rich artifacts—action traces and aria snapshots—so developers can prove flows work without writing a full test suite by hand. Environment variables control headed versus headless mode and where trace files land, which keeps local debugging practical on a laptop. Complexity is intermediate because you must trust the agent to interpret goals and you should still curate critical paths. This is browser automation infrastructure exposed via MCP, not a replacement for CI pipelines; combine it with your own assertions and deployment gates for production confidence.
- Goal-driven Playwright sessions orchestrated for LLM agents
- Full action traces plus aria-snapshots for accessibility-oriented review
- Headless default; COWORK_QA_HEADED=1 for visible Chromium debugging
- Session JSON traces stored under COWORK_QA_DATA or default .cowork-qa directory
- npm package cowork-qa-mcp v0.1.1 with stdio transport
Cowork Qa MCP by the numbers
- Data as of Aug 10, 2026 (Skillselion catalog sync)
claude mcp add --env COWORK_QA_HEADED=YOUR_COWORK_QA_HEADED --env COWORK_QA_DATA=YOUR_COWORK_QA_DATA cowork-qa-mcp -- npx -y cowork-qa-mcpAdd your badge
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| Package | cowork-qa-mcp |
|---|---|
| Transport | STDIO |
| Auth | None |
| Last updated | May 6, 2026 |
| Repository | inSideos-designs/cowork-qa-mcp ↗ |
What it does
Run goal-driven Playwright browser QA from your LLM agent with full action traces and aria snapshots for reproducible test evidence.
Who is it for?
Best when you want LLM-guided E2E checks on staging URLs with traceable session artifacts.
Skip if: Skip if you need managed cloud browser grids, load testing, or zero-local Playwright setup.
What you get
After install, your agent can complete browser goals and persist trace plus aria-snapshot files you can replay or audit.
- Completed browser sessions driven toward a natural-language goal
- Per-session JSON traces under configured data directory
- Aria-snapshots and action logs suitable for review or follow-up fixes
By the numbers
- Package version 0.1.1
- Identifier cowork-qa-mcp on npm
- Default trace path <cwd>/.cowork-qa
README.md
cowork-qa-mcp

A Model Context Protocol server that gives an LLM a real Chromium browser, records every action it takes toward a stated goal, and hands back a structured trace so the LLM (or a second LLM) can decide whether the goal was actually achieved.
Built on Playwright. Five tools, one binary, no cloud dependency.
Why
Most browser-tool MCP servers are stateless — the LLM clicks, gets HTML back, repeats. There's no record of what happened, no way to grade the run after the fact, and no goal context.
cowork-qa-mcp flips that:
- Every session starts with a goal in plain English.
- Every action (
goto,click,fill,press,eval) is recorded with timestamps, the URL after, and the page's aria-snapshot. - When the session ends, a JSON trace is persisted to disk and exposed via a single
qa_get_tracecall.
The orchestrating LLM can then reason over the trace ("did this run actually fulfill the goal, or did it click the wrong button?") instead of trusting the run-time chatter.
Tools
| Tool | What it does |
|---|---|
session_start |
Open a fresh tab, optional starting URL, return a session id |
session_act |
Run one of: goto, click, fill, press, eval. Records the step. |
session_observe |
Return current URL + full aria-snapshot of the page |
session_end |
Close the tab, persist the trace to disk, return the file path |
qa_get_trace |
Return the goal, every step, final URL, and final aria-snapshot — formatted for an LLM to read |
Install
Requires Node 20+. The package is on npm — no clone needed.
# Try it once, no install
npx cowork-qa-mcp
# Or install globally
npm install -g cowork-qa-mcp
The first install pulls Chromium via Playwright's postinstall (~150 MB).
Wire into your MCP-compatible client
Claude Code
claude mcp add cowork-qa --scope user -- npx -y cowork-qa-mcp
To watch the browser instead of running headless:
claude mcp add cowork-qa --scope user \
-e COWORK_QA_HEADED=1 \
-- npx -y cowork-qa-mcp
Verify with /mcp inside a fresh claude session — you should see cowork-qa ✓ connected and 5 tools.
Claude Desktop
Add to ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or %APPDATA%\Claude\claude_desktop_config.json (Windows):
{
"mcpServers": {
"cowork-qa": {
"command": "npx",
"args": ["-y", "cowork-qa-mcp"]
}
}
}
Cursor / Windsurf / other MCP clients
Any client that speaks the MCP stdio transport works. Point its server config at npx -y cowork-qa-mcp.
From source (for development)
git clone https://github.com/inSideos-designs/cowork-qa-mcp.git
cd cowork-qa-mcp
npm install
npm run build
node dist/server.js # stdio server, expects an MCP client
MCP Registry
This server is also published on the official MCP Server Registry as io.github.inSideos-designs/cowork-qa — clients that auto-discover from the registry will find it without any manual config.
Environment variables
| Variable | Default | Purpose |
|---|---|---|
COWORK_QA_HEADED |
unset (headless) | Set to 1 to launch Chromium with a visible window |
COWORK_QA_DATA |
<cwd>/.cowork-qa |
Directory where <session-id>.json traces are written |
Usage example
A typical end-to-end loop the orchestrating LLM runs:
session_start({ goal: "find the cheapest 14\" MacBook Pro on apple.com",
url: "https://www.apple.com/shop/buy-mac/macbook-pro" })
→ { session_id: "abc-123" }
session_observe({ session_id: "abc-123" })
→ URL + aria-snapshot
session_act({ session_id: "abc-123", action: "click",
target: "button:has-text('Continue')" })
# ... more acts / observes ...
session_end({ session_id: "abc-123" })
→ { steps: 7, trace_path: "~/.cowork-qa/abc-123.json" }
qa_get_trace({ session_id: "abc-123" })
→ Goal: ...
Steps (7 total): ...
Final URL: ...
Final aria-snapshot: ...
Trace format
Each trace is a JSON file:
{
"session_id": "abc-123",
"goal": "...",
"steps": [
{
"t": 142,
"action": "click",
"args": { "target": "...", "value": null },
"url_after": "...",
"aria_after": "..."
}
],
"final": { "url": "...", "aria": "..." },
"path": "/.../abc-123.json"
}
Limitations / known quirks
session_observecalls don't show up in the trace's step count — onlysession_actcalls do. The final aria-snapshot is captured atsession_end.evalruns the JS expression but doesn't return the value to the caller — only side effects on the page are observable.- One Chromium process is shared across all sessions in a server instance; each session gets its own context (cookies, etc. are isolated).
- Selectors are passed straight to Playwright. CSS, text-selectors (
button:has-text("Send")), androle=selectors all work.
License
MIT — see LICENSE.
Contributing
PRs welcome. Keep it small: this is meant to stay a thin, auditable server.
Recommended MCP Servers
How it compares
MCP Playwright QA runner with traces, not a static lint skill or hosted browser farm.
FAQ
Who is Cowork QA for?
Developers using Claude Code or Cursor who want the agent to exercise real browsers and save session evidence.
When should I use Cowork QA?
Use it during ship and testing when validating flows, capturing regressions, or reviewing accessibility snapshots before release.
How do I add Cowork QA to my agent?
Install cowork-qa-mcp from npm, configure stdio MCP in your client, and optionally set COWORK_QA_HEADED and COWORK_QA_DATA.