radare2-mcp
This is an MCP server for integrating radare2 with AI assistants. It utilizes a direct stdin/stdout communication model, enabling seamless binary analysis and file exploration. The direct integration with AI assistants allows users to work more efficiently.
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radare2: Latest versionClaude Desktop: Latest versionInstallation
Installation
Prerequisites
Please specify required software and versions:Installation Steps
1. Install using r2pm
bash
$ r2pm -Uci r2mcp
Troubleshooting
Common Issues
Issue: Server won't start Solution: Check the versions of radare2 and Claude Desktop.Configuration
Configuration
Claude Desktop Setup
PressCMD + , in the Claude Desktop app to open Developer settings and edit the configuration file as described below.
Location of Claude Configuration File
~/Library/Application Support/Claude/claude_desktop_config.json%APPDATA%\Claude\claude_desktop_config.json~/.config/Claude/claude_desktop_config.jsonConfiguration File Content
Add the following to your configuration file:json
{
"mcpServers": {
"radare2": {
"command": "r2pm",
"args": ["-r", "r2mcp"]
}
}
}
Examples
Examples
Basic Usage
Here are basic usage examples for the MCP server:Using with Claude Desktop
Available tools from this MCP server:
- tool1: Description of tool1
- tool2: Description of tool2
Programmatic Usage
javascript
// JavaScript example (Node.js)
const { MCPClient } = require('@modelcontextprotocol/client');
const client = new MCPClient();
await client.connect();
// Execute tool
const result = await client.callTool('toolName', {
parameter1: 'value1',
parameter2: 'value2'
});
console.log(result);
Use Cases
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AI Distiller is ultra‑fast, open‑source tool for intelligently extracting only the essential public APIs, types, and structure from large codebases. Compresses 90–98% of code into AI‑friendly context, integrates via CLI or MCP, supports 12+ languages, and AI prompt workflows for cleaner, cost‑effective AI development.
This project was completed during my Operating Systems course. The concept of the project is take an input file that lists various commands that should be performed by the CLI and would execute if they are valid commands with valid arguments. The project adds a multi process feature by having multiple processes working on the input file and thus increasing the efficiency of the application. All the code was written using C.