Jadx AI MCP vs Agentward

In-depth architectural comparison of the Jadx AI MCP and Agentward MCP servers. Compare execution transports, security boundaries, tool capabilities, quality scores, and ready-to-paste client installation snippets for Claude, Cursor, Windsurf, and VS Code.

Which MCP Server Should You Choose?

Choose Jadx AI MCP when:

• You need dedicated capabilities in the Security domain.
• You prefer local stdio subprocess transport architecture.
• Your security boundary fits: No auth required (Free / Open Source).
• Primary tools included: Exposes selected JADX-GUI classes over MCP, Retrieves Java source and smali code, Lists project classes, methods, and fields.

Explore Jadx AI MCP Details

Choose Agentward when:

• You need dedicated capabilities in the Security domain.
• You prefer local stdio subprocess transport architecture.
• Your security boundary fits: No auth required (Free / Open Source).
• Primary tools included: read_file, read_text_file, read_media_file.

Explore Agentward Details

Feature & Specification Comparison

Specification	Jadx AI MCP zinja-coder Security	Agentward agentward-ai Security
Summary	JADX-AI-MCP is a plugin and MCP Server for the JADX decompiler that integrates directly with Model Context Protocol (MCP) to provide live reverse engineering support with LLMs like Claude.	Permission control plane for AI agents. MCP proxy that enforces least-privilege YAML policies on every tool call, classifies sensitive data (PII/PHI), detects dangerous skill chains, and generates compliance audit trails. Supports stdio and HTTP proxy modes.
Category & Scope

Tools & Capabilities Breakdown

Ready-to-Paste Client Configurations

Paste either (or both) of these JSON server blocks into your client config file (e.g. claude_desktop_config.json or ~/.cursor/mcp.json).

{
  "mcpServers": {
    "zinja-coder-jadx-ai-mcp": {
      "command": "npx",
      "args": [
        "-y",
        "zinja-coder-jadx-ai-mcp"
      ]
    }
  }
}

{
  "mcpServers": {
    "agentward-ai-agentward": {
      "command": "uvx",
      "args": [
        "agentward"
      ]
    }
  }
}

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