"Automating a QA End-to-End Workflow" matching MCP servers:

Enables checking project files like Dockerfile, .nvmrc, and CI workflows to determine whether pinned runtime, database, and OS versions are still supported, providing end-of-life dates, latest patches, and upgrade targets for 470+ products.

Enables users to record, review, verify, and expose permitted browser workflows as callable MCP tools with typed inputs, isolated Chromium verification, and approval-gated writes.

Analyzes Playwright test results to provide structured QA insights, including test metrics, failure analysis, bug report drafts, and release-quality recommendations.

mcp-test-runner is an MCP server that lets your AI client (Claude / Cursor / Codex / Gemini) drive your entire QA loop end-to-end: * Run tests across pytest / Jest / Cypress / Go / Maestro — single MCP surface, one env var to switch * Analyze a URL (Web DOM probe) or a live mobile screen (Maestro hierarchy) to extract testable modules + candidate cases * Generate runna

An MCP server for the comprehensive analysis of Swagger 2.0 and OpenAPI 3.x contracts. It allows users to extract detailed information about endpoints, request/response schemas, parameters, and security configurations from API documentation.

Evaluates MCP servers by running read-only checks and returning a graded report with an A-F letter grade.

An MCP server that brings senior-QA discipline to AI coding assistants, enabling test planning, TDD, mutation testing, and code review.

Enables an AI assistant to author algorithm storyboards, workflow maps, and UI styling through MCP, serving a local web app for visualizing and reviewing them.

MCP server for end-to-end QA automation: generates test scenarios, discovers Playwright locators, creates TypeScript test code, executes tests, and creates GitHub issues for failures.

Enables AI agents to drive native 1C TestClient QA automation over stdio or authenticated streamable-HTTP transports, running BDD/Gherkin scenarios, reading and verifying managed forms, and performing target-bound lifecycle and UI operations. It also supports JUnit/Allure reporting and an optional authenticated Windows host bridge for desktop input and screenshots.

A standalone runtime and MCP server that executes Claude Code dynamic workflow files through interchangeable agent providers, ensuring compatibility with Claude Code's workflow format.

Enables AI agents to lint and format n8n workflow JSON over MCP, reporting issues with line-level detail and applying safe fixes.

Lets any MCP-capable coding agent read and update an app's QA memory, test-case catalogs, coverage gaps, and Playwright run history. It exposes 11 tools covering status, scanning, case lookup, next-ID generation, memory search/add/forget, and result ingestion.

Enables AI agents to crawl live DOMs into compact accessibility maps, generate frontend and backend test plans, execute self-healing Playwright QA locally without token replay, and compile passing flows into native .spec.ts files.

Enables Claude Code to drive a local cockpit UI through task validation, planning, coding, pre-review, and publishing, using waiting tools that return when the user clicks or speaks.

Enables MCP clients such as Claude Desktop, Claude Code, and Cursor to discover node types, author and validate typed multi-agent workflow files, launch runs against a workspace, and retrieve run status, node outputs, and workspace change details.

MCP server providing three QA tools: parse JUnit XML reports, detect flaky tests across multiple runs, and evaluate quality gates with pass/fail decisions.

Provides structured spec-driven development workflow tools for AI-assisted software development with sequential spec creation (Requirements → Design → Tasks). Features a real-time web dashboard for monitoring project progress and managing development workflows.

Gives AI agents a real Chromium browser via Playwright to QA-test web apps, with pass/fail assertions, network mocking, recorded traces and reports, and safety guards that block live payment traffic. Test outcomes come back as explained verdicts suitable for review or email delivery.

Evidence-driven quality testing for Model Context Protocol servers. It connects as a real client, captures the complete model-facing contract, identifies agent-usability risks, measures context cost, and executes only explicitly approved target calls.

Enforces disciplined programming practices by requiring AI assistants to audit their work and produce verified outputs at each phase of development, following structured workflows for refactoring, feature development, and testing.

A specialized MCP server for QA engineering. It provides tools for user story analysis, test strategy, BDD/Gherkin scenarios, contract testing, integration tests, performance plans, security checklists, and CI/CD pipeline generation, accessible from any MCP-compatible IDE or client.

An intelligent MCP server that helps development teams maintain high-quality project documentation by providing an AI-powered workflow for creating comprehensive specifications through requirements, design, and implementation documents.

An MCP server for issue-driven GitLab development, automating requirement analysis, issue creation, branching, coding, merge requests, and issue updates.

Enables Cursor users to track local workflow state and receive contextual nudges, daily summaries, and Windows toast notifications for sessions, edits, MCP usage, and plans.

MCP server for Plane, including self-hosted Plane. Lets Claude Code, Codex, Cursor and other agents plan, start, and complete Plane work items under your team's rules, with dry-run previews, idempotent creates, project briefings, and factual completion records. Install: uv tool install plane-workflow-mcp

Enables local Copilot use to interact with SDLC workflow tools (workflow tasks, internal-readiness, epic/ticket/repo-task, change-request, and journey) via a stdio MCP server that proxies to a local Workflow Service.

An MCP server that guides QA and verification processes by breaking down tasks into manageable steps and providing LLM-driven, confidence-scored tool recommendations.

A local MCP server that gives Cursor Agent three focused QA tools for analyzing user stories, creating test charters, and drafting bug reports, with built-in safety rules and reusable workflows.

Enables bounded, multi-phase coding workflows inside Codex that plan, implement, independently review, repair, and verify repository changes, with an inline dashboard for inspecting runs.