Playwright Report MCP
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Alternatives to Playwright Report MCP
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Related Servers
AlicenseNot gradedqualityBmaintenanceEnables querying Playwright test failure reports and execution results directly from AI assistants, allowing retrieval of test outcomes, failures, and report details.MIT- AlicenseNot gradedqualityAmaintenanceEnables AI agents to run, debug, and inspect Playwright end-to-end tests, returning structured pass/fail stats, failure diagnostics with actionable fix hints, live DOM inspection, selector validation, visual diffs, and flakiness verdicts instead of raw test output.342 npmMIT
- FlicenseAqualityBmaintenanceEnables AI assistants to summarize Playwright test runs, identify flaky tests, heuristically triage failures, generate Playwright test stubs, and retrieve recent GitHub CI status through MCP tool calls.5-
- AlicenseNot gradedqualityAmaintenanceEnables coding agents to validate web pages and run repeatable JSON browser scenarios, returning pass/fail results with local Playwright evidence such as screenshots, traces, and JUnit XML.26 npm1Apache 2.0
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- AlicenseNot gradedqualityCmaintenanceEnables AI agents to perform one-shot triage of Playwright trace files, pinpointing root causes like backend API failures or locator issues and generating self-healing code fixes in a single low-token call.MIT
TDQS
Scored across 2 tools
get_failures and get_test_summary have clearly distinct purposes: one retrieves only failed tests, the other an aggregate summary. There is no overlap or ambiguity between them.
Both tools follow a consistent get_[noun] pattern, making the naming predictable and easy to infer. The convention is uniform across the entire set.
With only two tools, the set is on the thin side and falls into the borderline range. The tools are focused and justified, but the count is minimal for a server that could reasonably include more report-oriented operations.
For a server scoped to the latest Playwright test run, get_failures and get_test_summary cover the primary reporting needs. Minor gaps exist—such as retrieving test details or run history—but they do not create dead ends for the core use case.