AI Dev SDK Overview

This document describes how to integrate and use the AiDev module to connect your Spryker application to AI development tools through the Model Context Protocol (MCP).

Overview

The AiDev module provides an MCP server that enables AI assistants to interact with your Spryker application. It exposes Spryker-specific information through MCP tools, allowing AI assistants to better understand and work with your codebase.

The module includes:

• MCP Server: A console command that runs an MCP server to communicate with AI assistants
• Extension Points: Plugin interfaces for adding custom MCP tools
• Built-in Tools: Pre-configured tools for accessing Spryker transfers, interfaces, and OMS information

Console commands

The AiDev module provides the following console commands:

MCP Server Command

The ai-dev:mcp-server command starts an MCP server that allows AI assistants to interact with your Spryker application.

docker/sdk console ai-dev:mcp-server -q

This command:

• Starts an MCP server using stdio transport
• Registers all configured MCP tool plugins
• Listens for requests from AI assistants

Usage: This command is typically configured in AI assistant tools (like Claude Desktop) to enable them to access Spryker-specific information.

Setup Command

The ai-dev:setup command sets up AI tooling for your Spryker project. It generates rules, an agents/context file, and skills — all tailored to the selected AI tool.

docker/sdk console ai-dev:setup

The command automatically detects the AI tool installed in your project and prompts you to confirm or select a different one. It then generates the following for the selected tool:

• Rules: Coding conventions and architectural guidelines.
• Agents/context file: Project-specific context for AI agents.
• Skills: Reusable task-specific AI skill files.

Output modes

The command supports two output modes:

• Ready to use: Files are generated directly in the tool-specific directories listed in the table below.
• Example: Files are generated in example directories — for example, .claude/rules-example/ instead of .claude/rules/. Rename the directories when ready to use.

Output locations by AI tool

Codex CLI does not have a native rules format. When you select it, the command offers to generate rules in another tool’s format instead and places them in that tool’s rules directory.

!/.github

Usage: Run this command once when setting up AI tooling for a project.

Claude Code plugin

The AI Dev SDK ships a Claude Code plugin — spryker-ai-dev-sdk — through the spryker-plugins-official marketplace. The plugin bundles Spryker-aware skills and the spryker-code-reviewer subagent. See Claude Code Plugin for installation instructions and a full list of capabilities.

Extension points

The AiDev module provides plugin interfaces for extending the MCP server with custom functionality:

AiDevMcpToolPluginInterface

Implement this interface to add custom MCP tools that AI assistants can use to query or interact with your application.

Interface location: SprykerSdk\Zed\AiDev\Dependency\AiDevMcpToolPluginInterface

Integration: Register your tool plugins in AiDevDependencyProvider::getMcpToolPlugins():

<?php

namespace Pyz\Zed\AiDev;

use SprykerSdk\Zed\AiDev\AiDevDependencyProvider as SprykerAiDevDependencyProvider;
use Pyz\Zed\AiDev\Communication\Plugins\CustomAiDevMcpToolPlugin;

class AiDevDependencyProvider extends SprykerAiDevDependencyProvider
{
    /**
     * @return array<\SprykerSdk\Zed\AiDev\Dependency\AiDevMcpToolPluginInterface>
     */
    protected function getMcpToolPlugins(): array
    {
        return array_merge(parent::getMcpToolPlugins(), [
            new CustomAiDevMcpToolPlugin(),
        ]);
    }
}

Configuration

The AiDev module can be configured through the AiDevConfig class. Refer to the module’s configuration class for available options and their default values.

Debugging the MCP server

Before connecting your MCP server to AI assistants, you can test and debug it using the MCP Inspector tool. The inspector provides a web interface to interact with your MCP server, test tools, and verify that everything works correctly.

Using the MCP Inspector

Navigate to your Spryker project directory and run:

npx @modelcontextprotocol/inspector docker/sdk console ai-dev:mcp-server -q

This command:

• Starts the MCP Inspector in your browser
• Connects to your local MCP server
• Displays all available tools
• Lets you test tool calls interactively

With Xdebug:

npx @modelcontextprotocol/inspector docker/sdk cli -x console ai-dev:mcp-server