"Java command reference and usage" matching MCP servers:

MCP server for querying OpenAI usage and cost data, including spend summaries, daily breakdowns, month-over-month comparisons, and token usage by model.

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

Provides a structured map of 120 practical AI prompts across 6 business domains, enabling users to quickly generate complete prompts for specific tasks using slash commands or tools.

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

An MCP server that helps AI agents comprehend a codebase by providing tools for navigating, searching, and understanding code structure and history.

Enables Claude to execute Minecraft commands and get tab completions through the MasterControl API. Allows remote command execution and command discovery while the player is online on a server.

Enables async-first working practices by providing tools to draft decision docs, convert meetings to async artifacts, score status updates, and triage sync vs async tasks. It also offers reference tools for the Open and Async book's principles and coaching prompts.

A tool for detecting and cleaning Java memory shells via local or SSH remote execution. It enables AI agents to scan Java processes, analyze suspicious class code, and safely remove memory shells after user confirmation.

Enables building and evaluating LangGraph agents over a protocol-level MCP server to measure failure rates across four agent topologies.

Generates and manages slash commands for AI coding assistants like Claude Code and Cursor, supporting both interactive CLI and programmatic MCP access.

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

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.

A local-first, multi-provider cost meter for LLM usage, exposed as MCP tools. Captures every call into a local SQLite ledger and lets any coding agent query spend, compare providers, and get recommendations — no cloud, no account. First-class support for Chinese providers (Qwen, DeepSeek) alongside Anthropic and OpenAI.

Enables AI agents and MCP clients to convert currency amounts, retrieve current, historical, and timeseries exchange rates, and list supported currencies from European Central Bank reference data.

An MCP server for tracking and managing AI command usage history using a PostgreSQL database. It enables users to log, search, and view statistics for various AI-related commands and their execution contexts.

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.

Monitor failing GitHub Actions workflows, auto-fix them with OpenCode, and retry the run — driven by a workflow_run webhook, coordinated through an MCP server.

Enables LLMs to read and write local user data, generate fake users via sampling, and interact with structured prompts and resources.

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

Enables discovering and independently validating scholarly metadata from extracted research text using Crossref, OpenAlex, DataCite, and optional read-only Zotero checks, returning ranked and verified reference candidates.