What is frida-mcp?

41/100
Trust Score (E)
⚠️ Use Caution

frida-mcp is a infrastructure that A Frida dynamic instrumentation server based on the Model Context Protocol (MCP), allowing AI models (such as Claude, Gemini, etc.) to perform dynamic analysis for mobile and desktop applications thro. It has a Nerq Trust Score of 41/100 (E). 4 GitHub stars. Published by Nihility-Protoss. Last analyzed September 2026.

Why This Score

Trust & Safety Overview

41
TRUST SCORE
E
GRADE
4
STARS
0
DOWNLOADS

What frida-mcp Does

frida-mcp is a tool in the infrastructure category. A Frida dynamic instrumentation server based on the Model Context Protocol (MCP), allowing AI models (such as Claude, Gemini, etc.) to perform dynamic analysis for mobile and desktop applications through a standardized interface.. It is published by Nihility-Protoss and has no specified license. With 4 GitHub stars and 0 downloads, it has a small community of users and contributors.

Who Should Use frida-mcp

frida-mcp is recommended only for experimental use. Consider alternatives with higher trust scores for production systems.

Details

AuthorNihility-Protoss
Categoryinfrastructure
LicenseNot specified
TypeTool
SourceView on GitHub
Security Score0/100
Activity Score1/100

How to Get Started

Check the trust score before installing:

curl nerq.ai/v1/preflight?target=frida-mcp

Setup guide · Full safety report · Production review · Is it safe?

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Frequently Asked Questions

What is frida-mcp used for?
frida-mcp is a infrastructure tool. A Frida dynamic instrumentation server based on the Model Context Protocol (MCP), allowing AI models (such as Claude, Gemini, etc.) to perform dynamic analysis for mobile and desktop applications thro.
Is frida-mcp free?
License: Check project page. frida-mcp has 4 GitHub stars.
Is frida-mcp safe?
frida-mcp has a Nerq Trust Score of 41/100 (E). Evaluate carefully.
What are alternatives to frida-mcp?
Top alternatives: n8n, langflow, dify. See full comparison.

Last updated September 2026. Trust scores based on automated analysis of public data.

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