"Resources and tools for test automation" matching MCP servers:

Gives AI assistants structured access to a test automation stack so they can run suites, inspect failure details and captured output, look up test data, and file Jira bugs (or drafts) only for confirmed defects. It works with any framework that emits JUnit XML, letting assistants triage flaky, environment, and test-data issues alongside real product defects.

A comprehensive server that integrates mobile testing frameworks with JIRA, generating BDD test scenarios and framework-compatible test scripts automatically.

Exposes AI agents as MCP tools to fetch Jira stories, generate BRDs and Playwright test scripts, run tests, and auto-heal broken locators. Integrates with Claude Desktop and Cursor IDE for enterprise-grade test automation.

Enables AI-powered web test automation with self-healing locators and automatic GitHub checkin.

Enables AI agents to operate the Unreal Editor via MCP: reading, creating, and editing blueprints at the node level, authoring materials and UMG widgets, auditing projects, and verifying runtime behavior in PIE with read-back checks.

Enables AI-driven testing and automation of Tauri desktop applications through natural language, allowing users to interact with UI elements, capture screenshots, execute commands, and test application flows without manual clicking or complex scripts.

Enables coverage-driven test generation for RHDH plugin forests by analyzing git diffs and coverage reports, recommending the cheapest test layer, and emitting actionable test briefs, including Playwright MCP prompts for UI gaps.

Enables coding agents to deterministically audit test files for fake or fragile tests (no assertions, tautological or swallowed assertions, focused/skipped tests, fixed sleeps, real network calls) and to run the project's actual test runner, treating an exit-0 run with zero tests as a failure and flagging changed source files that lack test coverage.

MCP server that performs mutation testing and diff scoping to score how trustworthy tests are for detecting regressions in changed code.

A comprehensive testing server for validating MCP scanner tools and implementations, providing diverse tools, resources, and prompts that exercise various aspects of the Model Context Protocol specification.

A lightweight MCP test server for verifying client connectivity, providing tools, resources, and prompts for integration.

A TypeScript-based test implementation for the Model Context Protocol (MCP) with example configurations and Jest test cases. Provides a development foundation for building and testing MCP server functionality.

A demo MCP server for testing and debugging tools, providing tools to get launches and trending words.

Lets AI agents ask which tests a Playwright or Vitest project contains, which are skipped and why, by reading the test source files statically. Nothing is executed, written, or sent over the network, and answers come back as paged JSON with summaries, filters, and scan diagnostics.

An automated testing MCP server that converts test cases into a fixed JSON format, runs them case-by-case, and provides a visual report with review support for cases that cannot be automatically judged.

An MCP server that gives AI coding agents the ability to analyze a Python repository's test health: coverage, flaky tests, and ML-based pull-request risk prediction.

Enables AI coding agents to run Foundry tests and builds and receive compact, structured failure reports with decoded reasons, fuzz counterexamples or invariant call sequences, logs, and short traces. It also distinguishes genuine test failures from cases where tests did not run, returning actionable errors instead of false zero-failure results.

Test coverage intelligence MCP server for TypeScript and JavaScript projects. Analyzes coverage reports to find untested functions, computes cyclomatic complexity, and suggests test cases locally.

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.

A specialized testing harness that enables AI assistants to thoroughly test other MCP servers by connecting to them, discovering their tools/resources/prompts, executing test calls, and performing end-to-end validation with LLM integration.