
Frida
Provides dynamic instrumentation capabilities for mobile and desktop applications through the Frida toolkit. Allows you to inject code, monitor processes, and analyze running applications in real-time.
Enables dynamic instrumentation of mobile and desktop applications through Frida toolkit, providing capabilities for process management, device enumeration, and script injection for application analysis and debugging workflows.
What it does
- Attach to running processes on mobile and desktop
- Inject JavaScript code into applications
- List and manage processes across devices
- Monitor application behavior in real-time
- Execute interactive JavaScript REPL sessions
- Spawn and control application instances
Best for
About Frida
Frida is a community-built MCP server published by dnakov that provides AI assistants with tools and capabilities via the Model Context Protocol. Frida enables dynamic instrumentation and debugging for mobile and desktop apps, offering advanced process management an It is categorized under developer tools.
How to install
You can install Frida in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.
License
Frida is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.
Frida MCP
A Model Context Protocol (MCP) implementation for Frida dynamic instrumentation toolkit.
Overview
This package provides an MCP-compliant server for Frida, enabling AI systems to interact with mobile and desktop applications through Frida's dynamic instrumentation capabilities. It uses the official MCP Python SDK to enable seamless integration with AI applications.
Demo
https://github.com/user-attachments/assets/5dc0e8f5-5011-4cf2-be77-6a77ec960501
Features
- Built with the official MCP Python SDK
- Comprehensive Frida tools exposed through MCP:
- Process management (list, attach, spawn, resume, kill)
- Device management (USB, remote devices)
- Interactive JavaScript REPL with real-time execution
- Script injection with progress tracking
- Process and device monitoring
- Resources for providing Frida data to models
- Prompts for guided Frida analysis workflows
- Progress tracking for long-running operations
- Full support for all MCP transport methods
Installation
Prerequisites
- Python 3.8 or later
- pip package manager
- Frida 16.0.0 or later
Quick Install
pip install frida-mcp
Development Install
# Clone the repository
git clone https://github.com/yourusername/frida-mcp.git
cd frida-mcp
# Install in development mode with extra tools
pip install -e ".[dev]"
Claude Desktop Integration
To use Frida MCP with Claude Desktop, you'll need to update your Claude configuration file:
-
Locate your Claude Desktop configuration file:
- macOS:
~/Library/Application Support/Claude/claude_desktop_config.json - Windows:
%APPDATA%\Claude\claude_desktop_config.json - Linux:
~/.config/Claude/claude_desktop_config.json
- macOS:
-
Add the following to your configuration file:
{
"mcpServers": {
"frida": {
"command": "frida-mcp"
}
}
}
Usage
Once installed, you can use Frida MCP directly from Claude Desktop. The server provides the following capabilities:
Process Management
- List all running processes
- Attach to specific processes
- Spawn new processes
- Resume suspended processes
- Kill processes
Device Management
- List all connected devices (USB, remote)
- Get device information
- Connect to specific devices
Interactive JavaScript REPL
- Create interactive sessions with processes
- Execute JavaScript code in real-time
- Monitor process state and memory
- Hook functions and intercept calls
- Capture console.log output
- Handle errors and exceptions gracefully
Script Injection
- Inject custom JavaScript scripts
- Track injection progress
- Handle script errors and exceptions
Resources
- Get Frida version information
- Access process list in human-readable format
- Access device list in human-readable format
Development
# Clone repository
git clone https://github.com/yourusername/frida-mcp.git
cd frida-mcp
# Install development dependencies
pip install -e ".[dev]"
License
MIT
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