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