"Tools and Resources for Accelerating Java Backend and Frontend Development" matching MCP servers:

Provides AI assistants with frontend development tools including component scaffolding, bundle analysis, accessibility checks, and responsive design guidance. Enables automated generation of React components with tests and stories, bundle optimization recommendations, and WCAG compliance fixes.

Provides comprehensive code analysis (quality, complexity, linting, dependencies, security) and web scraping capabilities (static/dynamic content, API discovery) for development workflows.

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.

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

A zero-dependency local MCP server that audits and auto-fixes React/Next.js frontend code smells, unused imports, and responsive UI issues

An MCP server that provides tools for frontend development, including i18n issue detection, OpenAPI type generation, and project structure analysis.

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

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

A comprehensive MCP server for frontend analysis. It provides Google Lighthouse audits, code quality checks, SEO metadata verification, accessibility analysis, and bundle optimization for React and Next.js projects.

Enables AI agents to perform read-only static analysis of Node.js backend projects, detecting database query anti-patterns, async bottlenecks, connection pooling mistakes, and dependency hygiene issues while returning structured evidence-backed findings.

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.

Provides comprehensive development tools for FastMCP projects including documentation access, NPM package version management, and TypeScript type definitions retrieval. Enables developers to fetch FastMCP documentation, analyze NPM packages, and access MCP architecture information through natural language.

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

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.

MCP server for Next2D application development that generates code following MVVM + Clean Architecture + Atomic Design patterns, validates architecture, and provides API references.

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.

Enables AI agents to analyze and scaffold React/Next.js applications enforcing Feature-Sliced Design (FSD) conventions, providing tools for project analysis, rule retrieval, and entity generation.

A local, read-only MCP server that analyzes Python backend projects by providing tools to scan, map, and selectively read files, reducing token usage for AI clients.