cowork-qa-mcp
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@cowork-qa-mcp Start a session to find the cheapest 14-inch MacBook Pro on apple.com"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
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.
Related MCP server: Agentic Browser
Tools
Tool | What it does |
| Open a fresh tab, optional starting URL, return a session id |
| Run one of: |
| Return current URL + full aria-snapshot of the page |
| Close the tab, persist the trace to disk, return the file path |
| 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-mcpThe 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-mcpTo watch the browser instead of running headless:
claude mcp add cowork-qa --scope user \
-e COWORK_QA_HEADED=1 \
-- npx -y cowork-qa-mcpVerify 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 clientMCP 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 |
| unset (headless) | Set to |
|
| Directory where |
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.
Available Tools
5 toolsqa_get_traceA
Return the full recorded trace (goal, every step, final URL, final aria-snapshot) so the calling LLM can judge whether the goal was achieved. Call session_end first.
Inputs: session_id (required).
session_actB
Perform a browser action in a session: goto | click | fill | press | eval.
Inputs: action (required), session_id (required), value, target.
session_endA
Close the session, persist the trace to disk, and return the path.
Inputs: session_id (required).
session_observeA
Return the current URL and aria-snapshot of the session's page.
Inputs: session_id (required).
session_startA
Open a fresh browser tab and start recording a goal-driven session.
Inputs: goal (required), url.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
Loading tool schema changelog…
TDQS
Scored across 5 tools
Each tool maps to a distinct phase of the session lifecycle (start, act, observe, end, retrieve trace), leaving no ambiguity about which tool to use. The purposes are clearly separated and non-overlapping.
Four of five tools follow a consistent session_<verb> pattern (start, act, observe, end), but qa_get_trace breaks this with a qa_ prefix and a different verb style. The deviation is minor and the intent remains clear.
The tool count of 5 is well-suited for a QA automation server, covering the essential workflow without superfluous or redundant tools. Each tool earns its place in the session lifecycle.
The tool set provides full lifecycle coverage from session start through actions, observation, ending, and trace retrieval. There are no obvious gaps for the intended goal-driven QA workflow.
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