Frida MCP server

Frida MCP provides an implementation of the Model Context Protocol (MCP) for the Frida dynamic instrumentation toolkit. This server enables AI systems to interact with mobile and desktop applications through Frida's capabilities, using the official MCP Python SDK for seamless integration with AI applications.

Installation

Prerequisites

• Python 3.8 or later
• pip package manager
• Frida 16.0.0 or later

Standard Installation

Install the package directly from PyPI:

pip install frida-mcp

Setting Up Claude Desktop Integration

To use Frida MCP with Claude Desktop:

1. 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

2. Add the following to your configuration file:

{
  "mcpServers": {
    "frida": {
      "command": "frida-mcp"
    }
  }
}

Usage

After installation, Frida MCP provides several capabilities through the MCP interface:

Process Management

Work with application processes using these functions:

• List all running processes
• Attach to specific processes by name or ID
• Spawn new processes
• Resume suspended processes
• Kill processes

Device Management

Interact with connected devices:

• List all connected devices (USB, remote)
• Get detailed device information
• Connect to specific devices

Interactive JavaScript REPL

For real-time interaction with target applications:

• 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

Script Injection

For more complex instrumentation:

• Inject custom JavaScript scripts into processes
• Track injection progress
• Handle script errors and exceptions

Available Resources

The server provides access to:

• Frida version information
• Process lists in human-readable format
• Device lists in human-readable format

These capabilities allow AI systems to perform dynamic analysis, monitor application behavior, and interact with applications at runtime through the structured MCP interface.

How to add this MCP server to Cursor

There are two ways to add an MCP server to Cursor. The most common way is to add the server globally in the ~/.cursor/mcp.json file so that it is available in all of your projects.

If you only need the server in a single project, you can add it to the project instead by creating or adding it to the .cursor/mcp.json file.

Adding an MCP server to Cursor globally

To add a global MCP server go to Cursor Settings > MCP and click "Add new global MCP server".

When you click that button the ~/.cursor/mcp.json file will be opened and you can add your server like this:

{
    "mcpServers": {
        "cursor-rules-mcp": {
            "command": "npx",
            "args": [
                "-y",
                "cursor-rules-mcp"
            ]
        }
    }
}

Adding an MCP server to a project

To add an MCP server to a project you can create a new .cursor/mcp.json file or add it to the existing one. This will look exactly the same as the global MCP server example above.

How to use the MCP server

Once the server is installed, you might need to head back to Settings > MCP and click the refresh button.

The Cursor agent will then be able to see the available tools the added MCP server has available and will call them when it needs to.

You can also explictly ask the agent to use the tool by mentioning the tool name and describing what the function does.