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    Enables AI agents to inspect Shadow Monitor capture files locally, with tools to load bundles, find errors, search network requests, and replay user actions.
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    MIT
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    Automates the conversion of Figma designs into TypeScript React components and integrates with GitHub to create pull requests for the generated code. It includes visual regression testing with Playwright and accessibility validation to ensure implementations match the original designs.
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    MIT
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    Connects AI coding assistants to Gaffer test history and coverage data to analyze project health, debug failures, and identify untested code areas. It enables tools to track test stability, cluster failures by root cause, and monitor code coverage trends across projects.
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    MCP server for VertaaUX.ai — run UX & accessibility audits, generate fixes, and monitor quality from your LLM or IDE. 38 tools covering the full audit-to-fix lifecycle across 7 UX categories.
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    MIT
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    AI-powered ServiceNow developer toolkit for Claude Code with 116 tools covering script generation, code review, portal and catalog development, notifications, user and group management, CRUD operations, dictionary overrides, data migration, bidirectional integrations, ATF testing, performance analysis, technical documentation, and issue diagnosis.
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    Enables interaction with Webhook.site to create, manage, and monitor endpoints for capturing HTTP requests, emails, and DNS lookups. It provides 16 tools for testing webhooks and inspecting incoming data through the Model Context Protocol.
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    MIT
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    An MCP server based on Puppeteer and Chrome DevTools Protocol for advanced browser debugging, performance analysis, and memory detection. It enables users to inspect DOM elements, monitor console errors, capture screenshots, and perform heap snapshot analysis through persistent browser connections.
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    Provides programmatic access to BlazeMeter's performance testing platform through MCP tools. Enables users to retrieve test runs, analyze performance data, view error reports, and manage testing resources via natural language interactions.
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    Python MCP server for Selenium WebDriver — 84 tools for browser automation, element interactions, assertions, self-healing locators, and codegen for Java TestNG / JUnit 5 / Cucumber / pytest / C# NUnit / Playwright and CI pipelines (GitHub Actions / Jenkins / GitLab CI). No ChromeDriver setup needed.
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    MIT
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    A testing server that demonstrates Model Context Protocol features, providing access to user data, todos, and system information through resources, tools for user management and calculations, and prompt templates for various analyses.
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    MCP server for Sorify QA testing platform, enabling AI agents to manage test suites, generate and run tests, and receive notifications through natural language commands.
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    Apache 2.0
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    A lightweight Python-based microservice that provides simple echo functionality, receiving messages and returning them back to the client for diagnostic and testing purposes within the MCP framework.
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    Apache 2.0