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Bridges AI models with WinDbg for crash dump analysis and live debugging using MCP.
Configuration
View docs{
"mcpServers": {
"svnscha-mcp-windbg": {
"url": "http://127.0.0.1:8000/mcp",
"headers": {
"_NT_SYMBOL_PATH": "SRV*C:\\Symbols*https://msdl.microsoft.com/download/symbols"
}
}
}
}You can run an MCP server that connects AI models with WinDbg to analyze Windows crash dumps and engage in live debugging. This server wraps around CDB and exposes a consistent MCP interface so your AI assistant can issue debugger commands, inspect dumps, and work with remote debugging targets through familiar clients.
You will interact with the MCP Windbg server through an MCP-enabled client. Start the server with a local transport for quick experiments or use an HTTP transport for remote access. Typical workflows include analyzing a crash dump, connecting to a remote debugging session, and processing multiple dumps to identify recurring patterns.
Prerequisites you need before installing the server:
Install the MCP Windbg server from PyPI and start using it in your environment.
pip install mcp-windbgList crash dump files available for analysis to quickly discover and select targets for investigation.
Open and analyze a selected crash dump to perform initial investigations and extract relevant data.
Close and clean up resources associated with an opened crash dump.
Connect to a remote debugging target to perform live debugging across machines.
Terminate remote debugging sessions and free associated resources.
Execute WinDbg commands or sequences to perform custom analysis and investigation.