Apps · Reverse-engineering plugin for Ghidra (needs a local model server)

GhidraMCP

by LaurieWired · Apache-2.0 · 11,844 GitHub stars

The most popular MCP server for Ghidra: lets a model decompile, rename and cross-reference code in an open project, or analyse a file headless.

macOSWindowsLinux

Get GhidraMCP

At a glance

Best for
Driving Ghidra from any MCP-capable chat app.
Inference engine
  • uses your MCP client’s model server
GPU support
None of its own: it talks to a llama.cpp or MLX LM server
Opens
  • GGUF
  • MLX
Features
  • MCP tools
  • Tool calling
Platforms
Runs inside Ghidra on macOS, Windows and Linux; the bridge needs Python 3.10+.

Install

macOS

Download the release zip, then in Ghidra choose File › Install Extensions

Windows

Download the release zip, then in Ghidra choose File › Install Extensions

Linux

Download the release zip, then in Ghidra choose File › Install Extensions

Then install its MCP bridge with pip install git+https://github.com/LaurieWired/GhidraMCP, connect an MCP client that runs a local model (such as LM Studio, Jan or OpenCode) and serve a model that supports tool calling. The plugin listens on localhost:8080 by default.

5 models on this site run in GhidraMCP

Models tagged for reverse engineering that support tool calling, with a GGUF or MLX build to serve locally. Raw decompilers such as LLM4Decompile run on their own in llama.cpp or LM Studio instead.

Model Made by Type Size Opens it as Quality tier
GLM-4.7 Flash (30B-A3B) Zhipu AI LLM 31B (3.0B active) GGUF or MLX 88
Devstral 2 (123B) Mistral AI LLM 125B GGUF or MLX 86
Qwen3 Coder 30B-A3B Alibaba LLM 31B (3.3B active) GGUF or MLX 78
Qwen3 30B-A3B Alibaba LLM 31B (3.3B active) GGUF or MLX 74
gpt-oss 20B OpenAI LLM 21B (3.6B active) GGUF or MLX 70

Alternatives

Which app should I use?

Estimates come from published hardware specs and our open formulas, not from running the model on your machine. Real speed varies with runtime, drivers and settings. Numbers marked “Measured” come from a linked benchmark.

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