"Resources and Techniques for Testing in React" matching MCP servers:

Enables AI assistants to write and debug integration tests by providing live access to DOM structure and executing code directly in test environments.

Code-aware browser testing agent — reads your codebase, understands functionality, tests every element, reports with screenshots. Works as MCP server for Cursor/Claude Code or standalone CLI.

Provides tools for frontend testing including code analysis, test generation, test execution, and React component testing for Jest and Cypress frameworks.

Enables submitting FMF-based test requests to Testing Farm and listing available OS composes for testing.

An LLM-driven API testing platform exposed over MCP, enabling declarative test definition and DAG-based execution.

Enables automated testing and coverage reporting for MCP services with test execution, file generation, and mock service creation. Provides comprehensive testing infrastructure including Jest integration, coverage reports, and health checks for the MCP ecosystem.

MCP server that enables AI agents to programmatically run tests, query results, and receive intelligent recommendations about test execution strategy.

Provides coding agents with visibility into test health through tools for flaky test detection, test quality linting, and LLM evaluation harness, enabling them to triage failures, review test quality, and check prompt changes for regressions.

Enables Claude Code to read and write issues on the Testing Platform via natural language, including listing projects, filtering issues, creating and updating issues, and adding comments.

Enables accessibility testing of websites and HTML content using axe-core and IBM Equal Access engines. Supports WCAG compliance checking, multi-viewport testing, and provides detailed violation reports with remediation guidance.

An MCP router that connects to multiple PagerDuty sandbox environments for testing integrations like PD+Teams, PD+Jira, and more.

Connects AI agents to a running React Native app so they can see the screen, tap and type, and inspect logs, network traffic, and state without any SDK or code changes. Composite tools let an agent run a whole interaction flow in a single call instead of one round trip per tap.

Provides comprehensive React Native development assistance with expert-level automated code remediation, security vulnerability fixes, performance optimization, and production-ready code generation. Includes testing suite generation, dependency management, and accessibility compliance tools.

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.

An MCP server that executes tox commands to run Python tests within a project using pytest, allowing users to run all tests or specific test groups, files, cases, or directories.

Enables AI agents to inspect why React components re-rendered, replay recorded browser interactions as performance scenarios in headless Chrome, and verify fixes against performance budgets.

Enables automation and monitoring of React Native apps by providing tools to tap, swipe, screenshot, inspect component state, profile renders, and mock network requests via MCP.

Enables natural-language chat-driven API testing, letting users upload API specs, run deterministic pytest checks against live targets, inspect results, create defects, and view failure trends.

A full-stack API automation testing server that parses OpenAPI/Swagger/Postman/HAR specs, generates comprehensive test scenarios and executable code, and provides AI-powered review and auto-fix.

Enables MCP-compatible clients to discover API endpoints from OpenAPI/Swagger specs, send HTTP requests, validate responses, and analyze status codes for automated API testing.

Analyzes Testing Farm jobs, checks job status, and investigates failures with detailed error information.

Enables AI agents and MCP clients to drive real Chrome, Edge, Brave, and Firefox browsers through native automation protocols. It exposes tools for navigation, page snapshots, form filling, clicks, screenshots, console/network inspection, and tab management.

Enables MCP clients to open websites, capture screenshots at multiple breakpoints, and run automated design audits for issues like overflow, small tap targets, low contrast, missing alt text, tiny text, and clipped content.

Enables AI agents and MCP hosts to drive a persistent headless Chromium browser through Playwright, navigating pages, mapping visible fields and actions, clicking, typing, scrolling, and capturing screenshots via stdio tool calls. It also powers a local AI Test Studio dashboard that generates and runs structured end-to-end test plans with assertions, per-step timing, and screenshot evidence.

Enables AI agents to inspect UI screen recordings as token-efficient image sheets with changed regions boxed, single-frame flicker flagged, and speech aligned to frames. Exposes watch_video and zoom_video tools so agents can pull dense keyframes across any time range or one sharp full-resolution frame, all processed locally.

A multi-language testing automation server that enables AI assistants to discover, plan, and execute tests across six major programming languages. It provides comprehensive tools for repository scanning, automated test execution, and detailed coverage reporting.

Enables AI agents to test Telegram bots by driving the official Telegram Web client in a real browser, allowing visual verification of bot responses, inline keyboards, and Mini Apps.

A Model Context Protocol (MCP) server that provides testing and debugging tools for Stripe integrations, including test clock management, customer and product management, and subscription testing.

Exposes browser-testing capabilities—including navigation, clicking, typing, form submission, verification, and screenshots—so clients can discover the supported Playwright actions. It also builds structured testing requirements from a supplied website and task description, ready for plan generation and execution.

A standardized MCP server designed for testing integration with the Des MCP Server Testing API. It allows AI agents to interact with testing endpoints using tools implemented via the Model Context Protocol.