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radareorg/r2mcp

by Various

MCP stdio server for radare2

R

MCP

radareorg/r2mcp

Added 1 June 2026

Overview

A Model Context Protocol server that exposes radare2's binary analysis capabilities via stdio, allowing LLMs to inspect and manipulate binaries through structured conversations. It bridges the gap between AI assistants and low-level reverse engineering by turning radare2 commands into callable tools.

Best for

Best for
Security researchers and reverse engineers who want to augment their workflow with LLM-driven binary analysis

Use cases

  • Reverse engineering binaries with conversational AI assistance
  • Automated vulnerability research and binary inspection
  • Interactive binary analysis through LLM-driven command execution

How to use

Tools exposed

  • r2pm
  • docker
  • make
  • meson
  • ninja

Tested with

OpenCode, Mai, VSCode, Claude, CLION, Claude Desktop, GitHub Copilot Chat, Zed

Example client config

[object Object]

Notes

A Model Context Protocol server that exposes radare2’s binary analysis capabilities via stdio, allowing LLMs to inspect and manipulate binaries through structured conversations. It bridges the gap between AI assistants and low-level reverse engineering by turning radare2 commands into callable tools.

243 stars on GitHub. Last updated 2026-06-01. Licensed MIT.

Use cases

  • Reverse engineering binaries with conversational AI assistance
  • Automated vulnerability research and binary inspection
  • Interactive binary analysis through LLM-driven command execution

Pros

  • Direct integration with radare2’s powerful analysis engine
  • Leverages the standard MCP protocol for broad AI tool compatibility
  • Lightweight stdio interface with no additional network dependencies

Cons

  • Requires familiarity with radare2 commands and its extensive ecosystem
  • Limited to architectures and file formats supported by radare2
  • Primarily designed for CLI use, lacking a graphical interface

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.

Pros

  • Direct integration with radare2's powerful analysis engine
  • Leverages the standard MCP protocol for broad AI tool compatibility
  • Lightweight stdio interface with no additional network dependencies

Cons

  • Requires familiarity with radare2 commands and its extensive ecosystem
  • Limited to architectures and file formats supported by radare2
  • Primarily designed for CLI use, lacking a graphical interface
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