"author:{result['url']}" matching MCP servers:

Agent Ready is an AI agent readability scanner — point it at any public URL and get back a 0–100 score plus per-check remediation hints for every failing check. This package wraps the same engine that powers agent-ready.dev as an MCP server, so Claude Desktop, Claude Code, Cursor, Cline, VS Code, and Windsurf can run scans inline and explain the results.

Test management over MCP: author test cases, run manual executions with per-case results, cut releases, and link automated tests to the cases they cover. Works against the hosted M00N Report service or a self-hosted instance.

MCP server exposing SuperAudit’s free website audit as a callable tool, enabling AI agents to audit any public URL and receive scores across SEO, security, legal, performance, and more. No API key required; respects rate limits and caches results.

Enables AI assistants to author, debug, and run Snowfakery data generation recipes through the Model Context Protocol.

WCAG-Compliance/wcagc-mcp lets an assistant run real axe-core accessibility scans through the user's own wcagc account, rather than guessing accessibility from markup it can see. Tools cover a single URL or PDF, a full-site crawl, saved multi-step journeys, and violation trends.

Core Web Vitals analysis powered by Lighthouse. Four tools: analyze a URL, compare two URLs, check against thresholds, or crawl an entire site. Works with Claude Code, Cursor, Windsurf, and any MCP-compatible AI tool.

Enables interaction with Xray Cloud and Data Center for test management, including authentication, GraphQL queries, test execution/plan management, and result import via MCP.

Point your coding agent at a URL and get a real-browser QA audit: broken signup/login/checkout flows, JS console errors, missing analytics, consent + security headers, mobile tap targets, and accessibility — returned as machine-verified findings graded A-F.

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

Exposes Great Expectations data-quality checks as MCP tools for LLM agents, enabling data loading, expectation definition, validation, and result interpretation.

This MCP server lets GitHub Copilot fetch Azure Boards work items by URL or ID and generate QA test cases from the ticket content.

Runs the free, independent before/after accessibility-overlay witness on any public URL to test if accessibility overlay widgets actually work.

Enables the execution and analysis of JMeter performance tests through MCP-compatible clients. It provides tools for running tests in non-GUI mode, identifying performance bottlenecks, and generating comprehensive insights and visualizations from result files.

Integrates TestRail with Claude Code to enable AI-assisted test management workflows, including project, suite, test case, test run, and result operations.

Enables integration with Xray Cloud APIs for comprehensive test management including creating and managing test cases, test executions, test plans, and test sets. Supports CI/CD automation and test result tracking through GraphQL APIs.

Enables AI assistants to author, validate, inspect, and submit Neon3 NUI Flow interfaces through the Neon3 runtime, while managing app projects and diagnosing service state.

ModelSafetyMCP is an MCP server for scanning machine learning model artifacts for unsafe serialization, malicious model patterns, risky packaging, URL-based artifact scanning, and directory-level triage.

MCP server for capturing real UI screenshots using Playwright. Provides tools to capture a URL or capture with login and selectors.

Production-ready MCP server for Allure TestOps, enabling test case, launch, test result, and test plan management via natural language.

Facilitates unified execution and result parsing for various testing frameworks, including Bats, Pytest, Flutter, Jest, and Go, through a Model Context Protocol interface.