"A repository for hosting and sharing Java libraries" matching MCP servers:

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

Enables AI-driven deployment of code to decentralized storage networks like Greenfield, IPFS, and Arweave, providing instantly accessible webpage domains.

A production-grade MCP server for managing git projects, offering dynamic tool selection and enterprise-grade security.

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.

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 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.

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.

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.

Provides intelligent codebase analysis, dependency scanning, architecture detection, security vulnerability scanning, and automatic documentation generation for modern development teams.

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.

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.

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.

Relays a result screenshot to Slack so you can review a coding agent's output without opening the app.

Enables coding agents to add a bounded semantic-judgment layer for routing, ranking, extraction, verification, and escalation, returning typed signals and review recommendations.

Provides over 1,000 creative ways to decline requests across four categories (polite, humorous, professional, and creative). The MCP server wraps a REST API to help users craft professional rejections through natural language interactions.