What dependencies and runtime are required?
The server requires Python 3, a virtual environment, and the packages listed in `requirements.txt`. Volatility3 is accessed via these dependencies; no separate Volatility3 installation is needed.
@Kirandawadi
Basic information
Volatility3 MCP Server for automating Memory Forensics
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"volatility3-mcp": {
"command": "python",
"args": [
"-m",
"venv",
"environ"
]
}
}
}Set up a memory dump file for analysis
Identify the operating system of the memory dump
Display all available Volatility3 plugins
Get detailed information about a specific plugin
Execute any Volatility3 plugin with custom arguments
List all running processes in the memory dump
View all network connections from the system
Examine files and resources accessed by a process
Scan memory for malicious patterns using YARA rules
Volatility3 MCP Server is a bridge that allows MCP clients such as Claude Desktop to interact with Volatility3, the advanced memory forensics framework. It enables LLMs to analyze memory dumps, detect malware, and perform sophisticated forensic tasks through a conversational interface.
Clone the repository, create a Python virtual environment, install dependencies from requirements.txt, then configure your MCP client. For Claude Desktop, add the server to claude_desktop_config.json with the path to the virtual environment’s Python and bridge_mcp_volatility.py. For Cursor, start the SSE server via python3 start_sse_server.py and point Cursor to http://127.0.0.1:8080/sse.
The server requires Python 3, a virtual environment, and the packages listed in `requirements.txt`. Volatility3 is accessed via these dependencies; no separate Volatility3 installation is needed.
Windows and Linux memory dumps are supported. macOS support was listed as “coming soon” in the README.
The server offers two transports: stdio (used by Claude Desktop via `bridge_mcp_volatility.py`) and SSE (used by Cursor via `start_sse_server.py`).
Available MCP tools include `initialize_memory_file`, `detect_os`, `list_plugins`, `get_plugin_info`, `run_plugin`, `get_processes`, `get_network_connections`, `list_process_open_handles`, and `scan_with_yara`.
All analysis is performed locally on the user’s machine; the README does not mention any remote data transmission. The memory dumps and results remain on the local system.
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