"Tools for Testing in Python and Java" matching MCP servers:

Provides testing and quality assurance tools for AI agents via MCP, enabling generation of test cases, mock data, API mocks, coverage analysis, and assertions.

Bridges agentic coding tools and live Java runtime behavior through a lightweight sidecar agent. Attaches directly to a running JVM to provide bytecode-level runtime signals for probe-verified inspection and deterministic debugging.

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.

Automates Java Maven testing workflows with decision table-based test generation, security vulnerability scanning, JaCoCo coverage analysis, and Git automation.

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.

Decompiles Maven dependencies into readable Java source directly inside your AI agent.

Enables Large Language Models to access and manipulate Autodesk Revit models through a pyRevit-based bridge and the Model Context Protocol.

Enables coding agents to perform Java semantic navigation, diagnostics, compilation, JUnit testing, debugging, coverage, affected-test discovery, and safe refactoring previews without modifying source files.

Enables to interact with Tsurugi RDBMS by executing SQL (DDL, DML, SELECT) and retrieving metadata through MCP.

A learning MCP server providing tools for OS info, file operations, weather, SQLite queries and resources for documentation and user profiles.

Enables automatic generation of explicit boilerplate methods (getter/setter/equals/hashCode/toString/constructors) for Java entity classes, replacing Lombok dependencies with visible, reviewable code.

Enables AI agents to perform local video, audio, and file operations inside an isolated workspace, including cutting/concat videos, extracting audio, transcribing, and managing files, with typed responses and background job support.

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

MCP server for testing GitHub Actions workflows locally using nektos/act.

Provides Java development capabilities through Eclipse JDT.LS, enabling symbol navigation, code diagnostics, workspace searching, and Javadoc access across Java projects.

A Codex MCP server that provides low-token Java semantic navigation using source indexing and optionally JDT Language Server for enhanced symbol, references, and diagnostics.

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

Enables AI assistants to look up Java class definitions and list dependencies from Maven projects by analyzing local JAR files via the Model Context Protocol.

A Java implementation of the GitHub MCP (Model Context Protocol) Server using Spring AI. This server provides MCP-compatible tools for interacting with the GitHub API.

Automates Java/Maven test generation, JaCoCo coverage analysis, and Checkstyle checking through MCP tools. Enables iterative improvement of test coverage and code style until quality goals are met.

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.

MCP server for amazon.in — cheapest in-stock, best-value picks, and price history links.

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 AI to analyze Java classes from Maven project dependencies, with support for decompilation strategies and configurable groupId mappings.

Enables AI coding agents to look up live JDK javadoc, Spring Boot reference sections, and Maven Central artifact metadata as clean markdown. It provides ranked search, caching, robots-aware throttling, and errors returned as suggestions instead of raising into the MCP layer.

Execute Python code via subprocess with timeout and error handling, returning stdout, stderr, and exit code.

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.

A lightweight, local-first MCP server for executing HTTP requests and managing API collections and environments without cloud dependencies. It enables testing APIs, handling authentication, and importing OpenAPI specifications directly within MCP-compatible workflows.

An MCP server that uses the CFR decompiler to convert Java .class and .jar files back into readable source code. It supports single-file, batch, and recursive directory decompilation with automated CFR tool management.

This MCP server provides direct access to ruff linting, formatting checks, and ty type-checking for Python projects, with token-efficient, structured output.

A high-performance MCP server that bridges AI agents with Java codebases, providing professional-grade Java language intelligence via Eclipse JDT.LS.

Enables building, starting, stopping, restarting, inspecting, and monitoring registered Spring Boot + Maven projects on macOS, including status checks and log tailing through MCP tools.

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

Query Langfuse traces, schema and datasets, scores and metrics, debug exceptions, analyze sessions, and manage prompts. Full observability toolkit for LLM applications.

Enables AI tools to analyze Java dependencies by scanning Maven projects, decompiling JAR files, and extracting detailed class information including methods, fields, and inheritance relationships. Solves the problem of AI hallucinations when generating code that calls external dependencies by providing accurate class structures through decompilation.

Enables access to Australian real estate data through the Realty In Au API, supporting property listings, agent/agency information, property details, school lookups, and property search with various filters.

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.