# Ghidra Headless MCP

> Ghidra Headless MCP — mrphrazer-ghidra-headless-mcp. Use this tool when you need to automate reverse-engineering tasks, such as disassembly, decompilation, and patching, in a sandboxed environment. It solves problems related to analyzing and understanding complex software systems, providing a catalog of over 200 specialized tools through the Model Context Protocol. The Ghidra Headless MCP takes in binary code and returns detailed analysis results, making it ideal for AI agents to perform deep reverse-engineering tasks.

Canonical page: https://skillsregistry.net/skills/mrphrazer-ghidra-headless-mcp  
JSON: https://api.skillsregistry.net/v1/skills/mrphrazer-ghidra-headless-mcp

## Description

A headless Ghidra server that enables AI agents to perform deep reverse-engineering tasks such as disassembly, decompilation, and patching via the Model Context Protocol. It supports extensive automation of analysis workflows in sandboxed environments through a catalog of over 200 specialized tools.

## Trust

- **Trust score (0–1):** 0.60
- **Verification tier:** unverified

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-08-08

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/lc8fbnnorx)
- **Repository:** <https://github.com/mrphrazer/ghidra-headless-mcp>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "mrphrazer-ghidra-headless-mcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/mrphrazer-ghidra-headless-mcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/mrphrazer-ghidra-headless-mcp/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt
