"Java Programming Language" matching MCP servers:

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 decompilation and reverse engineering of Java JAR files through multi-engine decompilation, candidate evaluation, Maven project structuring, AST-based deobfuscation, and bytecode comparison.

Decompiles Java .class files, packages, and JARs into readable source code, enabling AI assistants to inspect Java bytecode.

Enables AI assistants and developers to analyze code for language-specific best practices and idiomatic patterns across programming languages, CI automation, and configuration formats.

Enables inspection and analysis of project structures to detect languages, frameworks, entry points, and dependencies across multiple programming languages including Node.js, Python, PHP, Go, Java, and Rust.

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

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.

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

Provides 23 modular tools for competitive programming, including problem analysis, algorithm planning, code generation, verification, testing, code review, and learning assistance.

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 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.

A Model Context Protocol server that provides Azure Java SDK documentation to AI assistants, allowing them to access readme files with introductions, key concepts, and code samples.

Enables users to turn natural-language requests into validated, compilable Java test methods, grounded in a graph catalog to prevent hallucinated imports and ungrounded symbols.

Fetches and extracts comprehensive package documentation from multiple programming language ecosystems (JavaScript, Python, Java, etc.) for LLMs like Claude without requiring API keys.

Execute code in 8 programming languages via gVisor-sandboxed Docker containers. Supports Python, JS, TS, Go, Java, C++, C, and Bash.

MCP server that scans Maven project dependencies, decompiles Java class files, and provides class structure analysis to LLMs for accurate code generation.

Enables AI agents to identify what language text is written in, returning top matches, confidence scores, script detection, and character statistics via a pay-per-call x402 API without requiring an API key.

A comprehensive MCP toolkit for Java backend developers, providing 35 tools across 5 servers for database analysis, JVM diagnostics, migration assistance, Spring Boot monitoring, and Redis diagnostics.

A universal Model Context Protocol server in Java, enabling interaction with multiple LLMs (OpenAI, Gemini, Hugging Face) and databases (MongoDB) through a modular Spring Boot architecture.