jadx-ai-mcp: Plugin for JADX to integrate MCP server

by zinja-coder · MCP Server · ★ 3.0k

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Featured in: AI Reverse Engineering Tools

Security audit verdict: SAFE · quality 64/100

None of the 43 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 43 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

aijavallmmcpmcp-servermcp-serversmobilemodel-context-protocolmodel-context-protocol-serverspentesting

Quick Facts

Stars3,004
Forks281
LanguageJava
CategoryMCP Server
LicenseApache-2.0
Quality Score64/100
Open Issues4
Last Updated2026-10-19
Created2025-04-07
Platformsjava, mcp
Est. Tokens~22k

About jadx-ai-mcp

JADX-AI-MCP (Part of Zin MCP Suite) ⚡ Fully automated MCP server + JADX plugin built to communicate with LLM through MCP to analyze Android APKs using LLMs like Claude — uncover vulnerabilities, analyze APK, and reverse engineer effortlessly. ⭐ Contributors Thanks to these wonderful people for their contributions ⭐ ljt270864457

Compatible Skills

These tools work well together with jadx-ai-mcp for enhanced workflows:

  • java-sdk — semantic(0.28)+complementary+same_lang+similar_pop+shared_platform (55%)
  • reverse-engineering-assistant — semantic(0.36)+rare_topics+same_lang+similar_pop+shared_platform (47%)
  • sonarqube-mcp-server — semantic(0.32)+same_lang+similar_pop+shared_platform (46%)
  • spring-ai-mcp — semantic(0.30)+rare_topics+same_lang+similar_pop+shared_platform (45%)

jadx-ai-mcp alternative? Top 6 similar tools

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 43 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. It is a first-layer scan, not a manual audit — we say so rather than overstate it.

The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.

Sources & who's responsible:

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