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mcp-java-dev-tools

by nimbly-dev

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    • A
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      Сonnects to live JVMs via JDWP protocol, enabling LLM agents to autonomously debug Java applications — attach to a running process, pause threads, set breakpoints (including conditional), inspect stacks with auto-resolved object fields, evaluate methods, set variable values, and diagnose issues like deadlocks and hung queries.
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      32 PyPI
      1
      MIT
    • A
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      Enables coding agents to observe any running process — syscalls, CPU flamegraphs, thread stacks, sockets and file descriptors, packets, heap retainers, and container state — without breakpoints, restarts, or instrumentation. It turns output from local tools like strace, py-spy, perf, lsof, tcpdump, and gdb/lldb into structured findings that cite evidence, supporting guided triage of leaks, slowness, hangs, and crashes.
      100 npm
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      MIT
    • A
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      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.
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      MIT
    • A
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      Enables AI coding agents to dynamically inspect running software — API hooks, syscall summaries, memory inspection, and HTTP/TLS/DNS reconstruction from live traffic or pcaps — across Linux, macOS, and Android targets. Every finding is returned as a structured Evidence Record with observation, artifacts, confidence, and explicit limitations, so agents cite proof rather than guess.
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    • F
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      Provides AI coding agents with real-time visibility into local development runtime state, enabling them to tail application logs, inspect ports, monitor process metrics, and diagnose network errors.
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    • A
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      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.
      MIT