"Accessing A-Share Market Data" matching MCP servers:

A validation layer for AI coding assistants that enforces explicit LLM evaluations on plans, code diffs, and tests to ensure safer and higher-quality code.

MCP server for comparing JSON, XML, XLSX, CSV, and text data using expected templates, returning pass/fail with difference details.

An MCP server that mocks payments, third-party API responses, and test data to enable QA flows for donation, checkout, SIP, and subscription pages without depending on a live gateway.

Zero-Config, Fully AI-Managed End-to-End Testing for all code gen platforms.

Enables AI assistants to generate realistic, synthetic test data on demand, including valid PESELs, NIPs, addresses, and more across 27 EU countries, through two tools: list_generators and generate.

Probes your live API and classifies why each endpoint failed (root cause, evidence, and a calibrated confidence level), exposed over MCP so your AI assistant debugs from evidence instead of guessing. Works with FastAPI, Express, Next.js, tRPC, and GraphQL.

Enables editorial content QA over the Model Context Protocol with four local tools that analyze readability, AI-sounding language, SEO on-page factors, and produce full reports where every finding includes an actionable fix.

A reusable MCP server for QA automation testing that enables running tests across web apps, APIs, CLI tools, and more directly from Claude Desktop.

Compares Figma frames to live pages, checking colors, fonts, and border radii, and generates a shareable HTML report.

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

Provides an LLM with a real Chromium browser to perform web tasks, recording every action into a structured trace for later verification of goal completion.

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.

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

MCP server that generates ISO/IEC/IEEE 29119-3 compliant test plan drafts from project information, providing a structured resource for the standard's test plan outline and a tool for draft creation.

An MCP server that provides an LLM with a real Chromium browser via Playwright, recording every action taken toward a stated goal and producing a structured trace so the run can be audited for goal achievement.

Provides prompt templates and tools for mobile QA automation, including converting manual tests to Appium scripts, analyzing failures, and standardizing bug reports.

Generates comprehensive API test plans (positive, negative, and boundary/edge cases) from endpoint metadata using LLMs, and exports them as Excel files.

MCP server enabling Claude Code to capture screenshots of Windows applications through WSL2, allowing AI to diagnose UI errors and verify layouts.

Enables AI agents to manage Autotest AI projects, screens, test cases, and test runs through natural language commands.

Enables Claude to generate executable test cases from decision tables in CSV, JSON, or Markdown formats. Provides intelligent test planning guidance and generates Playwright/API test code with TypeScript support.