Heap Analyzer MCP Server

This repository provides a Python-based MCP (Model Context Protocol) server that exposes tools for analyzing JVM thread dumps:

• analyze_thread_dump: Parses a JVM thread dump text file and returns a summary of thread states and potential deadlocks.

• compare_thread_dumps: Parses two JVM thread dump text files and returns a comparison of thread state counts and deadlocks.

Prerequisites

• Python 3.9+

• pip (Python package installer)

Related MCP server: MCP Test Failure Analysis Server

Installation

Option 1: Clone and Build from Source (Recommended)

1. Clone the repository:

   git clone https://github.com/rajendrag/jvm-heap-analyzer-mcp.git
   cd jvm-heap-analyzer-mcp

2. Create and activate a virtual environment:

   python -m venv .venv
   source .venv/bin/activate  # On Windows: .venv\Scripts\activate

3. Build the wheel:

   pip install build
   python -m build

4. Install the package:

   pip install dist/heap_analyzer_mcp_server-0.1.0-py3-none-any.whl

Option 2: Development Installation

For development or if you want to modify the code:

git clone https://github.com/rajendrag/jvm-heap-analyzer-mcp.git
cd jvm-heap-analyzer-mcp
python -m venv .venv
source .venv/bin/activate  # On Windows: .venv\Scripts\activate
pip install -e .

Usage with MCP Clients

After installation, the server can be used with any MCP-compatible client. The console script heap-analyzer-mcp-server will be available in your PATH.

Claude Desktop Configuration

1. Locate your Claude Desktop config directory:

   • macOS: ~/Library/Application Support/Claude/

   • Windows: %APPDATA%\Claude\

2. Create or edit the claude_desktop_config.json file:

   {
     "mcpServers": {
       "heap-analyzer-mcp": {
         "command": "heap-analyzer-mcp-server",
         "args": []
       }
     }
   }

3. Restart Claude Desktop to load the new server configuration.

Generic MCP Client Configuration

For other MCP clients, use this configuration:

{
  "name": "heap-analyzer-mcp",
  "command": "heap-analyzer-mcp-server",
  "args": [],
  "env": {},
  "timeout": 120000
}

Alternative: Using Python Module Directly

If you prefer not to use the console script:

{
  "name": "heap-analyzer-mcp",
  "command": "python",
  "args": ["-m", "heap_analyzer_mcp"],
  "env": {}
}

Testing the Server

You can test the server manually to ensure it's working:

# Test that the server starts without errors
echo '{"jsonrpc": "2.0", "id": 1, "method": "initialize", "params": {}}' | heap-analyzer-mcp-server

# Test import functionality
python -c "from heap_analyzer_mcp.__main__ import main; print('✅ Server is working!')"

Available Tools

1. analyze_thread_dump

Analyzes a single JVM thread dump file.

Parameters:

• path (required): Path to the thread dump text file

• max_threads (optional): Maximum number of threads to analyze (default: 5000)

Example usage in MCP client:

{
  "path": "/path/to/thread_dump.txt",
  "max_threads": 5000
}

Example response:

{
  "summary": "Analyzed 4 threads (limit 5000). States: RUNNABLE=2, WAITING=2",
  "counts": {
    "RUNNABLE": 2,
    "WAITING": 2,
    "BLOCKED": 0,
    "TIMED_WAITING": 0,
    "NEW": 0,
    "TERMINATED": 0
  },
  "deadlocks": [
    {
      "threads": ["Thread-1", "Thread-2"],
      "monitor": "java.lang.Object@12345"
    }
  ]
}

2. compare_thread_dumps

Compares two JVM thread dump files and shows the differences.

Parameters:

• path_a (required): Path to the first thread dump file

• path_b (required): Path to the second thread dump file

• max_threads (optional): Maximum number of threads to analyze (default: 5000)

• diff_mode (optional): Level of detail in comparison (default: "full")

  • "summary": Returns only summary and notes

  • "states": Returns summary, counts, and deltas

  • "full": Returns all fields including deadlock details

Example usage in MCP client:

{
  "path_a": "/path/to/dump1.txt",
  "path_b": "/path/to/dump2.txt",
  "diff_mode": "full",
  "max_threads": 5000
}

Example response:

{
  "summary": "State deltas: RUNNABLE=+1, WAITING=-1; Deadlocks present only in A",
  "counts_a": {"RUNNABLE": 2, "WAITING": 2, "BLOCKED": 0, "TIMED_WAITING": 0, "NEW": 0, "TERMINATED": 0},
  "counts_b": {"RUNNABLE": 3, "WAITING": 1, "BLOCKED": 0, "TIMED_WAITING": 0, "NEW": 0, "TERMINATED": 0},
  "deltas": {"RUNNABLE": 1, "WAITING": -1, "BLOCKED": 0, "TIMED_WAITING": 0, "NEW": 0, "TERMINATED": 0},
  "deadlocks_a": [{"threads": ["Thread-1", "Thread-2"], "monitor": "java.lang.Object@12345"}],
  "deadlocks_b": [],
  "notes": "Deadlocks present only in A"
}

Sample Thread Dumps

The repository includes sample thread dumps in the tests/ directory that you can use for testing:

• tests/sample_thread_dump.txt

• tests/sample_thread_dump_2.txt

Development and Testing

Running Tests

1. Install test dependencies:

   pip install -e .[test]

2. Run tests:

   pytest -q

Alternative Testing (without MCP dependencies)

If you can't install MCP dependencies in your environment:

PYTHONPATH=src python3 -m pytest -q

This uses the tools adapter to test functionality without requiring the full MCP runtime.

Project Structure

jvm-heap-analyzer-mcp/
├── src/heap_analyzer_mcp/
│   ├── __init__.py
│   ├── __main__.py           # MCP server and tool implementations
│   ├── parser.py             # Core thread dump parsing logic
│   └── tools_adapter.py      # MCP tool behavior for testing
├── tests/                    # Test files and sample thread dumps
├── pyproject.toml           # Package configuration
└── README.md               # This file

Limitations and Notes

• File size limit: Thread dump files larger than 10MB are rejected for safety

• File access: Files must be accessible by the server process (consider file permissions)

• Thread limit: By default, analysis is limited to 5000 threads per dump

• Communication: The server uses stdio for communication with MCP clients

Troubleshooting

Server Won't Start

• Verify installation: heap-analyzer-mcp-server --help

• Check Python environment: which python and which heap-analyzer-mcp-server

• Try running directly: python -m heap_analyzer_mcp

Client Can't Connect

• Ensure the server binary is in your PATH

• Verify the client configuration file syntax

• Check that the virtual environment is activated when starting the client

• Look at client logs for specific error messages

Permission Issues

• Ensure thread dump files are readable by the server process

• On Windows, you may need to use full paths in the configuration

Import Errors

• Verify all dependencies are installed: pip list | grep mcp

• Try reinstalling: pip uninstall heap-analyzer-mcp-server && pip install dist/heap_analyzer_mcp_server-0.1.0-py3-none-any.whl

Contributing

1. Fork the repository

2. Create a feature branch

3. Make your changes

4. Run tests: pytest

5. Submit a pull request

License

This project is open source. Please check the repository for license details.