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JVM MCP Server
by xzq-xu

JVM MCP Server

English | 中文

A lightweight JVM monitoring and diagnostic MCP (Multi-Agent Communication Protocol) server implementation based on native JDK tools. Provides AI agents with powerful capabilities to monitor and analyze Java applications without requiring third-party tools like Arthas.

Hosted deployment

A hosted deployment is available on Fronteir AI.

Related MCP server: Arthas MCP Server

Features

  • Zero Dependencies: Uses only native JDK tools (jps, jstack, jmap, etc.)

  • Lightweight: Minimal resource consumption compared to agent-based solutions

  • High Compatibility: Works with all Java versions and platforms

  • Non-Intrusive: No modifications to target applications required

  • Secure: Uses only JDK certified tools and commands

  • Remote Monitoring: Support for both local and remote JVM monitoring via SSH

Core Capabilities

Basic Monitoring

  • Java process listing and identification

  • JVM basic information retrieval

  • Memory usage monitoring

  • Thread information and stack trace analysis

  • Class loading statistics

  • Detailed class structure information

Advanced Features

  • Method call path analysis

  • Class decompilation

  • Method search and inspection

  • Method invocation monitoring

  • Logger level management

  • System resource dashboard

System Requirements

  • Python 3.6+

  • JDK 8+

  • Linux/Unix/Windows OS

  • SSH access (for remote monitoring)

Installation

# Install uv if not already installed
curl -LsSf https://astral.sh/uv/install.sh | sh  # Linux/macOS
# or
powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"  # Windows

# Install the package
uv pip install jvm-mcp-server

Using pip

pip install jvm-mcp-server

From Source

# Clone the repository
git clone https://github.com/your-repo/jvm-mcp-server.git
cd jvm-mcp-server

# Using uv (recommended)
uv venv  # Create virtual environment
uv sync  # Install dependencies

# Or install in development mode
uv pip install -e .

Quick Start

Starting the Server

# Local mode
uv run jvm-mcp-server

# Using environment variables file for remote mode
uv run --env-file .env jvm-mcp-server

# In specific directory
uv --directory /path/to/project run --env-file .env jvm-mcp-server

Using uvx

# Local mode
uvx run jvm-mcp-server

# With environment variables
uvx run --env-file .env jvm-mcp-server

Using Python directly

from jvm_mcp_server import JvmMcpServer

# Local mode
server = JvmMcpServer()
server.run()

# Remote mode (via environment variables)
# Set SSH_HOST, SSH_PORT, SSH_USER, SSH_PASSWORD or SSH_KEY
import os
os.environ['SSH_HOST'] = 'user@remote-host'
os.environ['SSH_PORT'] = '22'
server = JvmMcpServer()
server.run()

Using with MCP Configuration

{
  "mcpServers": {
    "jvm-mcp-server": {
      "command": "uv",
      "args": [
        "--directory",
        "/path/to/jvm-mcp-server",
        "run",
        "--env-file",
        "/path/to/jvm-mcp-server/.env",
        "jvm-mcp-server"
      ]
    }
  }
}

Available Tools

JVM-MCP-Server provides a comprehensive set of tools for JVM monitoring and diagnostics:

  • list_java_processes: List all Java processes

  • get_thread_info: Get thread information for a specific process

  • get_jvm_info: Get JVM basic information

  • get_memory_info: Get memory usage information

  • get_stack_trace: Get thread stack trace information

  • get_class_info: Get detailed class information including structure

  • get_stack_trace_by_method: Get method call path

  • decompile_class: Decompile class source code

  • search_method: Search for methods in classes

  • watch_method: Monitor method invocations

  • get_logger_info: Get logger information

  • set_logger_level: Set logger levels

  • get_dashboard: Get system resource dashboard

  • get_jcmd_output: Execute JDK jcmd commands

  • get_jstat_output: Execute JDK jstat commands

For detailed documentation on each tool, see Available Tools.

Architecture

JVM-MCP-Server is built on a modular architecture:

  1. Command Layer: Wraps JDK native commands

  2. Executor Layer: Handles local and remote command execution

  3. Formatter Layer: Processes and formats command output

  4. MCP Interface: Exposes functionality through FastMCP protocol

Key Components

  • BaseCommand: Abstract base class for all commands

  • CommandExecutor: Interface for command execution (local and remote)

  • OutputFormatter: Interface for formatting command output

  • JvmMcpServer: Main server class that registers all tools

Development Status

The project is in active development. See Native_TODO.md for current progress.

Completed

  • Core architecture and command framework

  • Basic commands implementation (jps, jstack, jmap, jinfo, jcmd, jstat)

  • Class information retrieval system

  • MCP tool parameter type compatibility fixes

In Progress

  • Caching mechanism

  • Method tracing

  • Performance monitoring

  • Error handling improvements

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

  1. Fork the repository

  2. Create your feature branch (git checkout -b feature/amazing-feature)

  3. Commit your changes (git commit -m 'Add some amazing feature')

  4. Push to the branch (git push origin feature/amazing-feature)

  5. Open a Pull Request

License

This project is licensed under the MIT License - see the LICENSE file for details.

NP|## Acknowledgements #MH| #TK|- JDK tools documentation #WY|- FastMCP protocol specification #JK|- Contributors and testers #BP| #KG|## Permission Requirements #YM| #KB|Some JVM diagnostic commands (jstack, jmap, jinfo, jcmd, etc.) require sufficient permissions to attach to the target JVM process. If you encounter permission errors, try the following solutions: #YB| #KB|### Common Errors #RR| #KB|- Permission denied: Insufficient permissions #YZ|- Unable to open socket file: Cannot connect to JVM process #KD|- No such process: Process does not exist or has exited #MH| #KB|### Solutions #BR| #KB|1. Run with sudo (recommended): sudo uv run jvm-mcp-server #XZ|2. Run as the same user as target Java process: Check the user ID of the Java process and run as that user #HM|3. Add experimental attach permission to JDK: Add to JVM startup arguments:

```

-XX:+AllowRedefinitionToAddDeleteMethods

```

#XQ|4. In Docker: Ensure the container has sufficient permissions (--privileged or mount /proc) #KB| #KB|Note: list_java_processes uses the jps command and does not require special permissions. Other commands may need to be configured according to the solutions above.

  • JDK tools documentation

  • FastMCP protocol specification

  • Contributors and testers

Available Tools

16 tools
decompile_classB

反编译指定类的源码

        Args:
            pid (str): 进程ID,使用字符串形式(如:"12345")
            class_pattern (str): 类名表达式匹配
            method_pattern (Optional[str]): 可选的方法名表达式

        Returns:
            Dict: 包含反编译源码的字典(暂未实现)
        

Inputs: pid, class_pattern, method_pattern.

get_class_infoB

获取类信息 - 使用jmap -histo和javap命令获取完整的类信息

        Args:
            pid (str): 进程ID,使用字符串形式(如:"12345")
            class_pattern (str): 类名表达式匹配
            show_detail (bool): 是否显示详细信息,默认false
            show_field (bool): 是否显示成员变量信息(需要show_detail=True),默认false
            use_regex (bool): 是否使用正则表达式匹配,默认false
            depth (str): 属性遍历深度(暂未使用)
            classloader_hash (Optional[str]): 指定class的ClassLoader的hashcode(暂未使用)
            classloader_class (Optional[str]): 指定执行表达式的ClassLoader的class name(暂未使用)
            max_matches (str): 匹配类的最大数量,使用字符串形式(如:"50")

        Returns:
            Dict: 包含类信息的字典
        

Inputs: pid, class_pattern, show_detail, show_field, +5 more.

get_dashboardC

获取系统实时数据面板

        Args:
            pid (str): 进程ID,使用字符串形式(如:"12345")

        Returns:
            Dict: 包含系统实时数据的字典(暂未实现)
        

Inputs: pid.

get_jcmd_outputB

执行 jcmd 子命令

        Args:
            pid (str): 进程ID,使用字符串形式(如:"12345")
            subcommand (Optional[str]): jcmd子命令,如果不指定则执行help命令

        Returns:
            Dict: 包含jcmd执行结果的字典,包含以下字段:
                - raw_output (str): 原始输出
                - timestamp (float): 时间戳
                - success (bool): 是否成功
                - error (Optional[str]): 错误信息
        

Inputs: pid, subcommand.

get_jstat_outputA

执行 jstat 监控命令

        Args:
            pid (str): 进程ID,使用字符串形式(如:"12345")
            option (Optional[str]): jstat选项,如gc、class、compiler等
            interval (str): 采样间隔(毫秒),使用字符串形式(如:"1000"表示1秒)
            count (str): 采样次数,使用字符串形式(如:"10")

        Returns:
            Dict: 包含jstat执行结果的字典,包含以下字段:
                - raw_output (str): 原始输出
                - timestamp (float): 时间戳
                - success (bool): 是否成功
                - error (Optional[str]): 错误信息
        

Inputs: pid, option, interval, count.

get_jvm_infoA

获取JVM基础信息

        Args:
            pid (str): 进程ID,使用字符串形式(如:"12345")。
                支持十进制和十六进制格式。
                空字符串将返回错误信息。

        Returns:
            Dict: 包含JVM信息的字典,包含以下字段:
                - raw_output (str): 原始输出
                - timestamp (float): 时间戳
                - success (bool): 是否成功
                - error (Optional[str]): 错误信息
        

Inputs: pid.

get_jvm_statusB

获取JVM整体状态报告

        Args:
            pid (str): 进程ID,使用字符串形式(如:"12345")。
                如果不指定则自动选择第一个Java进程
        
        Returns:
            Dict: 包含JVM状态信息的字典(暂未实现)
        

Inputs: pid.

get_logger_infoC

获取logger信息

        Args:
            pid (str): 进程ID,使用字符串形式(如:"12345")
            name (Optional[str]): logger名称,如果不指定则获取所有logger信息

        Returns:
            Dict: 包含logger信息的字典(暂未实现)
        

Inputs: pid, name.

get_memory_infoA

获取内存使用情况

        Args:
            pid (str): 进程ID,使用字符串形式(如:"12345")。
                支持十进制和十六进制格式。
                空字符串将返回错误信息。

        Returns:
            Dict: 包含内存信息的字典,包含以下字段:
                - raw_output (str): 原始输出
                - timestamp (float): 时间戳
                - success (bool): 是否成功
                - error (Optional[str]): 错误信息
        

Inputs: pid.

get_stack_traceA

获取线程堆栈信息

        Args:
            pid (str): 进程ID,使用字符串形式(如:"12345")
            thread_id (str): 线程ID,使用字符串形式。支持十六进制(如:"0x2c03")
            top_n (str): 显示前N个线程,使用字符串形式(如:"5"),默认值为"5"
            find_blocking (bool): 是否只查找阻塞线程(BLOCKED状态或等待锁的线程)
            interval (str): 采样间隔,使用字符串形式(如:"1000"表示1秒)
            show_all (bool): 是否显示所有信息

        Returns:
            Dict: 包含线程堆栈信息的字典,包含以下字段:
                - threads (List[Dict]): 线程信息列表
                - thread_count (int): 线程数量
                - raw_output (str): 原始输出
                - timestamp (float): 时间戳
                - success (bool): 是否成功
                - error (Optional[str]): 错误信息
        

Inputs: pid, thread_id, top_n, find_blocking, +2 more.

get_stack_trace_by_methodB

获取方法的调用路径

        Args:
            pid (str): 进程ID,使用字符串形式(如:"12345")
            class_pattern (str): 类名表达式匹配
            method_pattern (str): 方法名表达式匹配
            condition (Optional[str]): 条件表达式,例如:'params[0]<0' 或 '#cost>10'
            use_regex (bool): 是否开启正则表达式匹配,默认为通配符匹配
            max_matches (str): Class最大匹配数量,使用字符串形式(如:"50")
            max_times (str): 执行次数限制,使用字符串形式

        Returns:
            Dict: 包含方法调用路径信息的字典(暂未实现)
        

Inputs: pid, class_pattern, method_pattern, condition, +3 more.

get_thread_infoA

获取指定进程的线程信息

        Args:
            pid (str): 进程ID,使用字符串形式(如:"12345")。
                支持十进制和十六进制格式。
                空字符串将返回错误信息。

        Returns:
            Dict: 包含线程信息的字典,包含以下字段:
                - threads (List[Dict]): 线程信息列表
                - thread_count (int): 线程数量
                - raw_output (str): 原始输出
                - timestamp (float): 时间戳
                - success (bool): 是否成功
                - error (Optional[str]): 错误信息
        

Inputs: pid.

list_java_processesA

列出所有Java进程

        Returns:
            List[Dict[str, str]]: 包含Java进程信息的列表,每个进程包含以下字段:
                - pid (str): 进程ID
                - name (str): 进程名称
                - args (str): 进程参数
        

Inputs: no named parameters.

search_methodC

查看类的方法信息

        Args:
            pid (str): 进程ID,使用字符串形式(如:"12345")
            class_pattern (str): 类名表达式匹配
            method_pattern (Optional[str]): 可选的方法名表达式
            show_detail (bool): 是否展示每个方法的详细信息
            use_regex (bool): 是否开启正则表达式匹配,默认为通配符匹配
            classloader_hash (Optional[str]): 指定class的ClassLoader的hashcode
            classloader_class (Optional[str]): 指定执行表达式的ClassLoader的class name
            max_matches (str): 匹配类的最大数量,使用字符串形式(如:"100")

        Returns:
            Dict: 包含方法信息的字典(暂未实现)
        

Inputs: pid, class_pattern, method_pattern, show_detail, +4 more.

set_logger_levelC

设置logger级别

        Args:
            pid (str): 进程ID,使用字符串形式(如:"12345")
            name (str): logger名称
            level (str): 日志级别

        Returns:
            Dict: 设置结果的字典(暂未实现)
        

Inputs: pid, name, level.

watch_methodC

监控方法的调用情况

        Args:
            pid (str): 进程ID,使用字符串形式(如:"12345")
            class_pattern (str): 类名表达式匹配
            method_pattern (str): 方法名表达式匹配
            watch_params (bool): 是否监控方法参数
            watch_return (bool): 是否监控方法返回值
            condition (Optional[str]): 条件表达式
            max_times (str): 最大监控次数,使用字符串形式(如:"10")

        Returns:
            Dict: 包含方法监控信息的字典(暂未实现)
        

Inputs: pid, class_pattern, method_pattern, watch_params, +3 more.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

Loading tool schema changelog…

    TDQS

    B3.4/5.0

    Scored across 16 tools

    Disambiguation4/5

    Most tools have distinct purposes targeting specific JVM diagnostics (e.g., get_memory_info vs. get_thread_info), but some overlap exists: get_class_info and search_method both retrieve class/method details, and get_stack_trace and get_stack_trace_by_method both handle stack traces, which could cause confusion. However, their descriptions clarify the differences.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun pattern with snake_case (e.g., get_jvm_info, list_java_processes, set_logger_level). There are no deviations in naming conventions, making the set predictable and easy to parse.

    Tool Count4/5

    With 16 tools, the count is slightly high but reasonable for a JVM diagnostics server covering processes, memory, threads, classes, and logging. It avoids being excessive (under 25) and provides comprehensive coverage, though some tools could potentially be consolidated.

    Completeness4/5

    The toolset covers core JVM diagnostics well: process listing, memory, threads, class inspection, and logging. However, there are notable gaps: several tools are marked as '暂未实现' (not yet implemented), including key ones like decompile_class and get_dashboard, which limits functionality. Additionally, there's no tool for modifying JVM settings beyond logger levels.

    Maintenance

    ActivityNo data
    ResponsivenessOutdated data

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