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

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 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.

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.

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 MCP clients to run read-only static audits on supplied n8n, Dify, Trigger.dev, Activepieces, and OpenAPI exports, and to screen HTTPS URLs for unsafe schemes, returning structured findings and limitations.

ocal-first, read-only MCP server that audits repository test architecture across ten language ecosystems. It returns deterministic evidence-backed findings, blockers, rankings, and repository-native test plans without modifying source files.

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.

Self-healing test automation MCP server that diagnoses and fixes issues in mobile and web apps, including a one-command vibe-check to prioritize broken functionality.

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 sophisticated server that enables AI assistants to automatically analyze codebases and generate comprehensive, professional documentation.

MCP server for automated code review using AI agents. It analyzes code diffs or file paths for bugs, security issues, and style violations.

Generates structured prompts for Claude Code to create comprehensive Terraform test cases including unit, integration, and mock tests.

Enables AI agents to safely read, search, and inspect a local git repository, including PR-style diffs and changed-file summaries. It also supports opt-in allowlisted test runs.

MCP server providing npm registry search, package details, dependency auditing, bundle size estimation, and package comparison tools for AI agents.

An intelligent MCP toolset for software testers that monitors code changes, analyzes test impact, recommends tests, and assesses risk, supporting multiple AI coding frameworks via dual transport modes.

An MCP server that provides a persistent sandbox for AI coding agents to explore codebases server-side, returning only compact summaries to reduce context consumption.

Contract-driven test enforcement and reporting for LLM-generated code via MCP, VS Code, Copilot CLI, Claude, Cursor, or Python SDK.

MCP server for IFS Cloud PL/SQL unit testing, enabling check of testability, generation of unit tests, and orchestration of deploy/run steps via ifs-f1-codegen-dev.

A Model Context Protocol server that helps programmers understand code by providing explanations, tech stack analysis, and best practice suggestions through prompt templates.