jadx-ai-mcp
Enables AI-assisted reverse engineering and code analysis within JADX, reducing time spent manually inspecting decompiled Android/Java bytecode and improving…
Plugin for JADX to integrate MCP server
- Ask Claude to decompile and analyze Android APK files through JADX integration
- Generate documentation for reverse-engineered Java code extracted from mobile applications
- Find security vulnerabilities in decompiled Android app source code with AI assistance
Enables AI-assisted reverse engineering and code analysis within JADX, reducing time spent manually inspecting decompiled Android/Java bytecode and improving security audit accuracy.
Security teams and mobile app auditors analyzing APK or compiled Java code with AI-powered contextual insights.
https://github.com/zinja-coder/jadx-ai-mcp
By zinja-coder
How to Get It
claude mcp add jadx-ai-mcp -- npx -y jadx-ai-mcp
Tip: Paste this into a Claude Code conversation. Verify command matches your Claude Code version.
Auto-generated from the tool's public listing — not hands-on verified. Cross-check against the source repo's README before running.
Once it’s connected, paste this into Claude:
Decompile and analyze Android APK files through JADX integration
Trust Signals Auto-scanned
Data & Access
Community Pulse Quiet
No community discussions found yet. This doesn't mean the tool isn't good — it may be new or serve a niche use case.
Reviewer notes
Auto-scanned review. These are observations, not a security certification.
Scored from trust signals (evidence-eval-v1): 2,817 GitHub stars; contributors unknown; last commit 0d ago; license Apache-2.0.
Things to check
- Scanned, not hands-on tested — this entry was auto-scanned from public metadata (GitHub metrics, license, security flags). No reviewer has run it, and no tool-specific limitations have been documented yet.
How to evaluate tools before deploying →
Data shown here comes from public APIs and automated scanning. Reviewer notes reflect one person's experience. This is not a security certification or legal recommendation. Always evaluate tools according to your own organization's policies.
Evaluation
Scored from trust signals (evidence-eval-v1): 2,817 GitHub stars; contributors unknown; last commit 0d ago; license Apache-2.0.