mame-mcp

mame-mcp

Enables MAME reverse engineering tasks including memory access tracing, input injection, ROM auditing, and IO-port discovery for arcade-to-SNES porting.

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README

mame_mcp

mame_mcp is a Model Context Protocol bridge for MAME-focused reverse engineering. It is aimed at arcade-to-SNES porting work: memory access traces, input injection, ROM audit checks, IO-port discovery, and reproducible headless harnesses.

This first cut is stock-MAME compatible. It drives MAME with generated -autoboot_script Lua sidecars instead of requiring a custom MAME binary. That keeps the useful tools available immediately; a deeper MAME source fork can be added later for live sockets, richer trace buffers, or debugger APIs that Lua cannot expose cleanly.

Quick Start

python -m pip install -e .

$env:MAME_EXE = "/path/to/mame"      # or leave unset if mame is on PATH

mame-mcp-tools --names
mame-mcp-tools --category trace

Wire it into Codex or another MCP client:

{
  "mcpServers": {
    "mame": {
      "command": "mame-mcp-bridge",
      "env": {
        "MAME_EXE": "/path/to/mame"
      }
    }
  }
}

Restart the MCP client after editing its config.

This repo includes a generic .mcp.json that only starts the bridge. Pass system and rompath in each tool call, or set MAME_SYSTEM and MAME_ROMPATH in your local MCP config for the project you are inspecting.

Tools

Current implemented tools:

Tool Purpose
ping Verify the MCP bridge is alive.
config_check Show resolved MAME executable, working directory, system, and ROM path.
audit_romset Run mame -verifyroms <system>.
get_ioports Boot a machine briefly and list MAME Lua IO-port fields.
trace_memory_access Generate a Lua read/write tap trace for one or more CPU address ranges.
trace_cchip_superman Optional Superman helper built on trace_memory_access; no ROM path is baked in.
run_lua_script Run a caller-supplied MAME Lua script headlessly.

The MCP responses return JSON text with command lines, log paths, return codes, stderr/stdout tails, and parsed trace summaries where applicable.

Environment

Env var Default Purpose
MAME_EXE mame MAME executable or command on PATH.
MAME_SYSTEM none Default machine short name, e.g. driver_short_name.
MAME_ROMPATH none ROM search path.
MAME_CWD current directory Working directory for generated scripts/logs and MAME state.
MAME_WORKDIR <MAME_CWD>/.mame_mcp Generated Lua, logs, nvram, cfg, etc.

Generic Trace Example

{
  "system": "driver_short_name",
  "rompath": "/path/to/roms",
  "frames": 1800,
  "ranges": [
    { "name": "device_window", "start": 9437184, "end": 9441279 }
  ],
  "trackReads": [
    { "name": "status", "address": 9439234 }
  ],
  "injectPreset": "none",
  "dryRun": true
}

trace_memory_access installs read/write taps over each range, dedupes by (R/W, PC, address, range), optionally counts values read from selected addresses, and writes a human-readable log plus a parsed JSON summary.

Use "dryRun": true to generate the Lua harness without launching MAME.

Superman C-Chip Helper

trace_cchip_superman is a convenience wrapper for the known Superman C-Chip window. It still requires the caller or environment to provide the ROM path.

{
  "rompath": "/path/to/roms",
  "frames": 1800,
  "injectPreset": "none"
}

It expands to a trace_memory_access call over $900000-$900FFF, tracking reads from $900802/$900803 and reporting whether status $01 and $05 were seen.

Fork Roadmap

The stock-MAME Lua layer can cover a lot:

  • address read/write taps,
  • frame callbacks,
  • input-field injection,
  • ROM audit and machine metadata,
  • screenshots via MAME command-line/video options,
  • reproducible generated scripts and logs.

A true MAME source fork becomes worthwhile when we need:

  • a long-lived JSON-RPC socket inside MAME,
  • debugger-grade live memory reads/writes without generated scripts,
  • instruction trace ring buffers with low overhead,
  • tile/sprite/sound device introspection not exposed through Lua,
  • stable save/load state and screenshot APIs as one-shot MCP calls.

The MCP tool names and response shapes here are intentionally similar to the Mesen MCP bridge so agents can learn one mental model and apply it to both console and arcade sources.

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