Plugin for JADX to integrate MCP server
⚡ Fully automated MCP server + JADX plugin built to communicate with LLM through MCP to analyze Android APKs using LLMs like Claude — uncover vulnerabilities, parse manifests, and reverse engineer effortlessly.
Image generated using AI tools.
JADX-AI-MCP is a plugin for the JADX decompiler that integrates directly with Model Context Protocol (MCP) to provide live reverse engineering support with LLMs like Claude.
Think: "Decompile → Context-Aware Code Review → AI Recommendations" — all in real time.
Watch the demo!
It is combination of two tools:
JADX MCP Server is a standalone Python server that interacts with a JADX-AI-MCP plugin (see: jadx-ai-mcp) via MCP (Model Context Protocol). It lets LLMs communicate with the decompiled Android app context live.
The following MCP tools are available:
fetch_current_class() — Get the class name and full source of selected classget_selected_text() — Get currently selected textget_all_classes() — List all classes in the projectget_class_source(class_name) — Get full source of a given classget_method_by_name(class_name, method_name) — Fetch a method’s sourcesearch_method_by_name(method_name) — Search method across classesget_methods_of_class(class_name) — List methods in a classget_fields_of_class(class_name) — List fields in a classget_method_code(class_name, method_name) — Alias for get_method_by_name //to be removedget_smali_of_class(class_name) — Fetch smali of class🔍 Basic Code Understanding
"Explain what this class does in one paragraph."
"Summarize the responsibilities of this method."
"Is there any obfuscation in this class?"
"List all Android permissions this class might require."
🛡️ Vulnerability Detection
"Are there any insecure API usages in this method?"
"Check this class for hardcoded secrets or credentials."
"Does this method sanitize user input before using it?"
"What security vulnerabilities might be introduced by this code?"
🛠️ Reverse Engineering Helpers
"Deobfuscate and rename the classes and methods to something readable."
"Can you infer the original purpose of this smali method?"
"What libraries or SDKs does this class appear to be part of?"
📦 Static Analysis
"List all network-related API calls in this class."
"Identify file I/O operations and their potential risks."
"Does this method leak device info or PII?"
🤖 AI Code Modification
"Refactor this method to improve readability."
"Add comments to this code explaining each step."
"Rewrite this Java method in Python for analysis."
📄 Documentation & Metadata
"Generate Javadoc-style comments for all methods."
"What package or app component does this class likely belong to?"
"Can you identify the Android component type (Activity, Service, etc.)?"
Note: Download both jadx-ai-mcp-<version>.jar and jadx-mcp-server-<version>.zip files.
# 0. Download the jadx-ai-mcp-<version>.jar and jadx-mcp-server-<version>.zip
https://github.com/zinja-coder/jadx-ai-mcp/releases
# 1.
unzip jadx-ai-mcp-<version>.zip
├jadx-mcp-server/
├── jadx_mcp.py
├── requirements.txt
├── README.md
├── LICENSE
├jadx-ai-mcp-<version>.jar
# 2. Install the plugin
# For this you can follow two approaches:
## 1. One liner - execute below command in your shell
jadx plugins --install "github:zinja-coder:jadx-ai-mcp"
## The above one line code will install the latest version of the plugin directly into the jadx, no need to download the jadx-ai-mcp's .jar file.
## 2. Or you can use JADX-GUI to install it by following images as shown below:
## 3. GUI method, download the .jar file and follow below steps shown in images
# 3. Navigate to jadx-mcp-server directory
cd jadx-mcp-server
# 4. This project uses uv - https://github.com/astral-sh/uv instead of pip for dependency management.
## a. Install uv (if you dont have it yet)
curl -LsSf https://astral.sh/uv/install.sh | sh
## b. OPTIONAL, if for any reasons, you get dependecy errors in jadx-mcp-server, Set up the environment
uv venv
source .venv/bin/activate # or .venv\Scripts\activate on Windows
## c. OPTIONAL Install dependencies
uv pip install httpx fastmcp
# The setup for jadx-ai-mcp and jadx_mcp_server is done.
Make sure Claude Desktop is running with MCP enabled.
For instance, I have used following for Kali Linux: https://github.com/aaddrick/claude-desktop-debian
Configure and add MCP server to LLM file:
nano ~/.config/Claude/claude_desktop_config.json
And following content in it:
{
"mcpServers": {
"jadx-mcp-server": {
"command": "/<path>/<to>/uv",
"args": [
"--directory",
"</PATH/TO/>jadx-mcp-server/",
"run",
"jadx_mcp_server.py"
]
}
}
}
Then, navigate code and interact via real-time code review prompts using the built-in integration.
hammer symbol and you should you see somthing like following:
fetch currently selected class and perform quick sast on it
This plugin allows total control over the GUI and internal project model to support deeper LLM integration, including:
Add Support for apktool
Add support for hermes code (ReactNative Application)
Add more useful MCP Tools
Make LLM be able to modify code on JADX
Add prompts templates, give llm access to Android APK Files as Resources
END-GOAL : Make all android reverse engineering and APK modification tools Connect with single MCP server to make reverse engineering apk files as easy as possible purely from vibes.
The files related to JADX-AI-MCP can be found under this repo.
The files related to jadx-mcp-server can be found here.
Kindly open an issue with respective template.
Tested on Claude Desktop Client, support for other AI will be tested soon!
This project is a plugin for JADX, an amazing open-source Android decompiler created and maintained by @skylot. All core decompilation logic belongs to them. I have only extended it to support my MCP server with AI capabilities.
The original README.md from jadx is included here in this repository for reference and credit.
This MCP server is made possible by the extensibility of JADX-GUI and the amazing Android reverse engineering community.
Also huge thanks to @aaddrick for developing Claude desktop for Debian based linux.
And in last thanks to @anthropics for developing the Model Context Protocol and @FastMCP team
JADX-AI-MCP and all related projects inherits the Apache 2.0 License from the original JADX repository.
Disclaimer
The tools jadx-ai-mcp and jadx_mcp_server are intended strictly for educational, research, and ethical security assessment purposes. They are provided "as-is" without any warranties, expressed or implied. Users are solely responsible for ensuring that their use of these tools complies with all applicable laws, regulations, and ethical guidelines.
By using jadx-ai-mcp or jadx_mcp_server, you agree to use them only in environments you are authorized to test, such as applications you own or have explicit permission to analyze. Any misuse of these tools for unauthorized reverse engineering, infringement of intellectual property rights, or malicious activity is strictly prohibited.
The developers of jadx-ai-mcp and jadx_mcp_server shall not be held liable for any damage, data loss, legal consequences, or other consequences resulting from the use or misuse of these tools. Users assume full responsibility for their actions and any impact caused by their usage.
Use responsibly. Respect intellectual property. Follow ethical hacking practices.
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