LibreAI / Agentes de IA / jadx-ai-mcp
// agents · zinja-coder/jadx-ai-mcp

jadx-ai-mcp

jadx-ai-mcp é um projeto de agentes de IA de código aberto de zinja-coder (zinja-coder/jadx-ai-mcp no GitHub). Tem 2.869 estrelas no GitHub e 264 forks, é publicado sob a licença Apache-2.0 e foi atualizado pela última vez no GitHub em 23 de setembro de 2026.

JADX plugin + MCP server that lets LLMs analyze Android APKs live — decompile, review, find vulnerabilities

★ 2,9 mil estrelas⑂ 264 forksApache-2.0atualizado set 2026
▦ visual: o README deste projeto não inclui nenhuma captura incorporável,
então aqui vai um marcador. O guia abaixo está completo mesmo assim.
// dados do projeto

Dados do projeto

Estrelas no GitHub
2.869
Forks
264
Licença
Apache-2.0
Última atualização no GitHub
23 de setembro de 2026
Categoria
Agentes de IA
Tipo de ficha
Guia de instalação completo
// como funciona

Como funciona

  1. Clarify your goal

    Have an APK you are authorized to analyze and a goal: understand its code, audit it, or hunt for vulnerabilities.

  2. Get the release

    Download jadx-ai-mcp-<version>.jar and jadx-mcp-server-<version>.zip from GitHub Releases and unzip them.

  3. Install and configure

    Install the plugin into JADX, set up the server environment with uv, and add the server to your MCP client (e.g. Claude Desktop) config.

  4. Run your first analysis

    Open the APK in JADX, then ask your LLM to fetch the current class or search for a suspicious API and explain it.

// recursos

Por que as pessoas gostam tanto

Live decompiled context

The LLM works against the APK currently open in JADX, not stale exported files.

Rich MCP toolset

Tools include fetch_current_class(), get_selected_text() and more for reading classes, methods and selected code (full list in the README/docs).

Vulnerability-oriented workflow

Designed for the decompile → context-aware code review → AI recommendation loop for security analysis.

Two-part architecture

A JADX GUI plugin (Java) talks over HTTP to a standalone Python MCP server (jadx_mcp_server.py, using fastmcp/httpx).

Part of Zin MCP Suite

Sits alongside the author's APKTool-MCP-Server and ZIN-MCP-Client projects.

Docs site

Full documentation is published at jadx-ai-mcp.readthedocs.io.

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// execute você mesmo

Execute você mesmo

  1. Clone the repo

    Clone the plugin repo (or download the release jar + server zip from Releases).

    git clone https://github.com/zinja-coder/jadx-ai-mcp.git
    cd jadx-ai-mcp
  2. Set up the MCP server

    Unzip the server, enter its directory and install its dependencies with uv as the README shows.

    cd jadx-mcp-server
    uv pip install httpx fastmcp
  3. Add to your MCP client

    Point your client at the server via uv run, restart the client, and open an APK in JADX.

    {
      "mcpServers": {
        "jadx-mcp-server": {
          "command": "/path/to/uv",
          "args": ["--directory", "/path/to/jadx-mcp-server/", "run", "jadx_mcp_server.py"]
        }
      }
    }
// casos de uso

O que você pode criar

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// perguntas frequentes

Perguntas frequentes

Who maintains JADX-AI-MCP?

zinja-coder maintains it, as part of the Zin MCP Suite, with many community contributors.

Is it free?

Yes, it is Apache-2.0 licensed. JADX itself is a separate open-source decompiler you install yourself.

Does it need a paid API key?

It works through your MCP client (such as Claude Desktop), so any model costs come from that client's plan or API key.

How does it compare to using JADX alone?

JADX alone decompiles; this plugin lets an LLM query and reason over the live decompiled context through MCP tools, speeding up review.

How do I get started?

Download the jar and server zip from Releases, install the plugin in JADX, set up the server with uv, and add it to your MCP client config.

// continue explorando

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// alternativas

Alternativas em Agentes de IA

Os outros projetos de Agentes de IA com mais estrelas no catálogo do LibreAI — a lista realista de alternativas se jadx-ai-mcp não for o ideal para você.

// mais em agents

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