"Java command reference and usage" matching MCP servers:

A Model Context Protocol server that connects AI agents to live Java processes via Alibaba Arthas, enabling real-time diagnostics, debugging, and performance analysis without code changes.

MCP server that wraps Cursor Enterprise API to enable AI agents to answer questions about team spending, usage, and model adoption.

A JVM monitoring and control platform server based on Arthas that provides a Python interface for monitoring and analyzing Java processes with capabilities for thread analysis, memory monitoring, and performance diagnostics.

Headless MCP server for Eclipse MAT that enables analyzing Java heap dumps using built-in commands, OQL queries, and predefined reports.

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

Enables querying Langfuse analytics, cost metrics, and usage data across multiple projects. Provides tools for trace analysis, model/service cost breakdowns, and daily usage trends through natural language queries.

Provides comprehensive telemetry and usage analytics for Claude Code sessions, including token usage tracking, cost monitoring, and tool usage patterns. Enables users to monitor their Claude usage with detailed metrics, warnings, and trend analysis.

Enables interaction with Google Cloud services including billing cost analysis, log querying, and metrics monitoring through natural language commands. Provides comprehensive tools for managing GCP resources, analyzing costs, detecting anomalies, and retrieving operational insights.

Lets AI agents diagnose and debug live Java applications by auto-discovering JVMs and attaching Arthas to run diagnostic commands like thread, trace, watch, and ognl.

Exposes rate-limit and usage data for AI coding agent CLIs as MCP tools, enabling querying of usage snapshots and reset times.

Enables local-first tracking of AI token usage and costs from Claude Code and OpenCode, answering queries about tokens, models, sessions, and cost through MCP tools and a CLI, with no network calls.

Surface Claude Code token usage, estimated cost, and plan-limit status in any MCP client. Enables agents to query usage data from local logs and Anthropic API.

A MCP server for tracking AI usage metrics and structured logs across applications. Monitor model calls, analyze usage patterns, track costs, and debug AI interactions.

Exposes the ConnectWise Command (Continuum) ITSupport247 Reporting API as MCP tools, enabling querying of sites, devices, patches, antivirus, performance, and more.

AI health checkups, token usage, LLM cost optimization, BYOK vault guidance, provider usage visibility, and read-only cleanup audits for MCP-capable agents.

MCP server that drives cdb.exe/kd.exe to provide WinDbg debugging to LLM agents, enabling crash dump analysis, live process debugging, kernel debugging, and a searchable command reference.

A command-line tool for monitoring and analyzing New Relic application metrics using MCP.

Claude Code token usage and cost visibility for MCP-capable agents.

Enables AI-powered centralized log monitoring and Q\&A for GCP Java microservices, allowing log query, service health checks, and anomaly detection through MCP tools.

MCP server that captures and exposes usage, cost, productivity, and activity metrics for local-first software engineering teams, including LLM token usage, cloud cost savings, and developer activity tracking.