About GDB MCP Server
MDB-MCP is an MCP server that lets an AI assistant drive GDB or LLDB for binary debugging and analysis. It suits developers and security researchers who need breakpoints, memory reads and stack inspection.
Key features
- 01Start GDB or LLDB debugging sessions
- 02Run any gdb or lldb command
- 03Interrupt a running program
- 04Terminate the program and close the session
- 05Check available debuggers and open sessions
Use cases
- 01Ask an AI assistant why a program crashes with a segfault
- 02Set breakpoints and inspect the call stack and memory
- 03Use GDB extensions such as pwndbg or GEF during analysis
MCP support
This project is an MCP server that provides tools such as debugger_status, debugger_start and debugger_command to MCP clients for controlling debugger sessions.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.
Tools
Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.
Details
From the project READMEMDB-MCP
An MCP server that gives your AI assistant a real debugger. It drives GDB or LLDB, so the assistant can set breakpoints, run your program, read memory and walk the stack the same way you would.
Install
You need uv and at least one debugger:
# Debian / Ubuntu
sudo apt install gdb lldb python3-lldb
# macOS (LLDB ships with the Xcode command line tools)
xcode-select --install
Then add the server to your client. For Claude Code:
claude mcp add mdb -- uvx --from git+https://github.com/smadi0x86/MDB-MCP mdb-mcp
For Claude Desktop, Cursor or Windsurf:
{
"mcpServers": {
"mdb": {
"command": "uvx",
"args": ["--from", "git+https://github.com/smadi0x86/MDB-MCP", "mdb-mcp"]
}
}
}
VS Code takes the same entry under "servers" in .vscode/mcp.json, with
"type": "stdio" added. On Windows with WSL, set "command": "wsl" and put the full
path to uvx at the start of args.
Tools
debugger_status which debuggers are usable, and the open sessions
debugger_start start a gdb or lldb session, optionally loading a program
debugger_command run any gdb or lldb command
debugger_interrupt pause a running program, like Ctrl-C
debugger_terminate kill the program and close the session
Everything else is a normal debugger command, so break main, bt, x/16gx $sp
and frame variable all work. Commands that resume the program wait for it to stop
(10 seconds by default, adjustable per call). If it is still running after that, the
assistant can interrupt it or keep waiting.
GDB is the default on Linux and LLDB on macOS. Either can be picked explicitly. GDB
loads your ~/.gdbinit, so pwndbg and GEF keep working.
Try it
make -C examples
Then ask your assistant why examples/crash segfaults (give it the absolute path).
Configuration
To use a debugger other than the one on your PATH, set it in the server's env in
your client config:
"env": {
"MDB_GDB_PATH": "gdb-multiarch",
"MDB_LLDB_PATH": "/opt/homebrew/opt/llvm/bin/lldb"
}
Troubleshooting
If LLDB shows up as unavailable, debugger_status tells you why. On Debian and
Ubuntu it is usually a missing python3-lldb, which has to match your LLDB version.
The program can't read from your keyboard. Feed it a file instead:
run < input.txt # gdb
process launch -i input.txt # lldb
If attaching to a running process fails on Linux, check
/proc/sys/kernel/yama/ptrace_scope. A value of 1 only allows debugging child
processes.
Security
A debugger can run shell commands (shell, python, platform shell, script),
and the programs you debug run as your user. Only debug code you trust, and keep
tool approval on for debugger_command unless you are in a sandbox.
Development
uv sync
uv run pytest # tests for a missing debugger are skipped
uv run ruff check . && uv run ruff format --check .
The demo above is recorded from real tool calls with demo/record.py. See the top of
that file for how to regenerate it.
License
GPL-3.0
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.
