"Java Programming Language" matching MCP servers:

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

Enables scanning Java (Maven) projects for known vulnerabilities via natural language, returning severity-sorted reports with CVSS scores and fix versions.

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

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.

Enables household members to use Alexa+ in their own language and script, with shared lists, reminders, devices, and messages stored as spoken and rendered for each person.

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.

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 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 language models to access Language Server Protocol functionality across 13 programming languages with automatic detection and zero configuration.

Token-efficient MCP server for multi-language project analysis (Java, TypeScript, JavaScript, Markdown, Python) with plugins, semantic search, and static analysis.

Provides linear programming (LP), mixed-integer programming (MIP), and quadratic programming (QP) optimization capabilities using the HiGHS solver, enabling AI assistants to solve complex optimization problems like production planning, logistics, and portfolio optimization.

Enables local, Docker-isolated code execution across six programming languages including Python, Rust, and TypeScript. It features pre-warmed container pooling, persistent sessions, and built-in support for machine learning libraries.

Exposes VSCode's Language Server Protocol features through MCP, enabling AI assistants to perform language-aware operations like symbol navigation, reference tracking, safe renaming, type information retrieval, and hover documentation across codebases.

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.

Enables asking natural-language questions about any GitHub repository and receiving answers grounded in the actual code, with read-only enforcement and automatic repository fetching.

Enables AI assistants to perform web and image searches through a Google Programmable Search Engine, with pagination, language/country filters, and safe search.

Connects AI assistants like Claude to PHP's XDebug debugger for runtime inspection, breakpoint control, and variable tracking, enabling natural language debugging of PHP applications.

Provides read-only access to live Bay Area transit data, including routes, stops, real-time departures, vehicle positions, and service alerts, for use by large language models.