Playwright Report MCP

An MCP (Model Context Protocol) server for running Playwright tests and reading structured results, failed test details, and attachment content — designed for AI agents doing test failure analysis.

Table of contents

• What it is
• What it is NOT
• Why
• Quick start
• Tools
• Attachments
• Installation
• Configuration
• Requirements
• Troubleshooting
• Development
• Cutting a release
• Contributing
• Release
• License

What it is

Playwright Report MCP gives an AI agent structured, token-efficient access to Playwright test outcomes. It runs your test suite, reads the JSON reporter output, and surfaces exactly what the agent needs: which tests failed, what the errors were, and the content of relevant attachments.

What it is NOT

There are many Playwright MCP servers that control a browser — they navigate pages, click elements, fill forms, and take screenshots. Playwright Report MCP is not one of those.

Why

The problem with existing approaches

Default reporters (list / dot) — Playwright's default reporters print human-readable output to stdout. Compact, but lossy: no attachment paths, no retry breakdown, no structured data.

HTML reporter (report.html) — A self-contained SPA bundle (typically 2–50 MB). Not machine-readable as text and exceeds any LLM context window.

Reading results.json directly — Works, but a full JSON report for even a small test suite is 10,000–20,000 tokens. For a failing test, most of that is passing test metadata you don't need.

What Playwright Report MCP does instead

• Filters results.json to only failed tests
• Returns structured, typed JSON the agent can act on immediately
• Exposes individual attachments by name so the agent fetches only what it needs
• Works on results produced by anyone — CI pipeline, a human, or the agent itself

Token cost comparison (one failed test in a 20-test suite)

Approximate input token counts based on Claude tokenization (~3–4 characters per token for mixed JSON/text content).

... View full README on GitHub