qa-mcp
Related Servers
Alternatives to qa-mcp
No user-submitted related servers found.
Related Servers
- FlicenseNot gradedqualityDmaintenanceEnables automated QA testing by running a pipeline of AI agents that generate test scenarios, architect test layers, write Playwright tests, and review code, all grounded in feature requirements and API contracts.-
- AlicenseCqualityBmaintenanceAutomates generation of QA artifacts such as API tests, E2E tests, and documentation exports. It supports REST Assured, Cypress, and Excel/Word document generation.51 npmMIT

Debugg AI MCPofficial
AlicenseAqualityAmaintenanceZero-Config, Fully AI-Managed End-to-End Testing for all code gen platforms.8295 npm68Apache 2.0- AlicenseAqualityAmaintenanceTurn any .NET test-automation solution into a queryable map in one SQLite file — features, steps, API clients, page objects, and their dependencies. Zero config, no AI, no network, 100% deterministic.4113MIT
- AlicenseAqualityAmaintenanceAI-powered exploratory QA agent. Explores web apps like a real user — 18 MCP tools for clicking, filling forms, and navigating. Automatically verifies that actions persist (fake deletes, failed edits). Runs 16 detection types including dead links, SEO, accessibility, and performance checks.292MIT
- FlicenseNot gradedqualityDmaintenanceA dual-track testing server that combines CLI test execution with Playwright-based browser testing and persistent SQLite logging. It enables automated test pipelines, Git integration, and evidence-based requirement generation to streamline the development lifecycle.-
TDQS
Scored across 7 tools
Each tool targets a distinct task: discovery, API tests, UI tests, flow tests, combined run, report reading, and diffing. There is no overlap in their purposes, and descriptions clearly delineate their roles.
All tools use a consistent qa_ prefix followed by a clear verb (discover, run_flows, run_api, run_ui, run_all, report, diff). The pattern is uniform and predictable, making it easy to infer tool functions from names.
Seven tools is well within the ideal range for a QA-focused server. Each tool covers a necessary step in the workflow without redundancy or bloat, making the set tightly scoped.
The tool surface covers the full QA lifecycle: discovering testable surface (qa_discover), executing different test types (flows, API, UI), running all together (qa_run_all), and then analyzing results via qa_report and qa_diff. There are no obvious dead ends or missing operations for the server's purpose.