MCP server
by dnakov
Frida enables dynamic instrumentation and debugging for mobile and desktop apps, offering advanced process management an
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.
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.
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.
MIT
Frida is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.
Add new capabilities to Claude beyond text generation
Example
Access external data sources, execute code, interact with tools and services
Transform Claude from chatbot to action-taking agent
Provide Claude with access to relevant context and data
Example
Load project documentation, access knowledge bases, query databases
Get more accurate, context-aware responses
Automate multi-step workflows combining AI and external tools
Example
Research → Summarize → Create document → Send notification
Complete complex tasks end-to-end without manual steps
Share your MCP server with the developer community
I recommend Frida for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
According to our notes, Frida benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
Useful MCP listing: Frida is the kind of server we cite when onboarding engineers to host + tool permissions.
I recommend Frida for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
Frida is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
Frida is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
Frida has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
Frida reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
Frida is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
Frida has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
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A Model Context Protocol (MCP) implementation for Frida dynamic instrumentation toolkit.
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.
https://github.com/user-attachments/assets/5dc0e8f5-5011-4cf2-be77-6a77ec960501
pip install frida-mcp
# 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]"
To use Frida MCP with Claude Desktop, you'll need to update your Claude configuration file:
Locate your Claude Desktop configuration file:
~/Library/Application Support/Claude/claude_desktop_config.json%APPDATA%\Claude\claude_desktop_config.json~/.config/Claude/claude_desktop_config.jsonAdd the following to your configuration file:
{
"mcpServers": {
"frida": {
"command": "frida-mcp"
}
}
}
Once installed, you can use Frida MCP directly from Claude Desktop. The server provides the following capabilities:
# Clone repository
git clone https://github.com/yourusername/frida-mcp.git
cd frida-mcp
# Install development dependencies
pip install -e ".[dev]"
MIT
Prerequisites
Time Estimate
15-60 minutes depending on server complexity
Steps
Troubleshooting
✓ Do
✗ Don't
💡 Pro Tips
Architecture
Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.
Protocols
Compatibility
✓ Use when
Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.
✗ Avoid when
Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.