Agento: Magento 2 Adobe Commerce MCP AI Assistant Agent

A powerful AI assistant for Magento 2 that helps you interact with your store’s data using natural language queries.

Microsoft CEO told us: Adobe Commerce SaaS and Shopify are Dead!

Welcome Agento: The AI Magento Agent Built by Ukrainian Engineers
The eCommerce world just changed forever.

Agento AI Magento Agent Git Hub repo is finally openly available: https://github.com/Genaker/AgentoAI

First, these Ukrainian innovators built an AI to control FPV drones and defend Europe. Now, they’ve turned their sights on a new mission — rescuing eCommerce world. They embedded AI directly with Magento’s raw data or using PyGento: Python powered Magento layer: https://lnkd.in/g7NbkaCC AI can execute it naively. The result? Agento — the AI-powered Magento Copilot. No more writing code on top of Magento’s outdated PHP 2 foundation. No more Hyvä, Amasty, or any other bloated third-party stack. Just your purest store data. Ask Agento what you want — it delivers.
No code. No clutter. No compromises. No Fees. 100% Pure-Open source.

At its essence, a Machine Learning as a Service Platform (MCP) is a cloud-based solution designed to simplify and accelerate the adoption of machine learning (ML), a core subset of AI. Unlike traditional approaches to ML, which demand significant in-house expertise, custom infrastructure, and time-intensive development cycles, MCPs offer a managed, end-to-end environment where businesses can build, customize, deploy, and maintain ML models with ease. Think of it as a turnkey solution for AI — one that abstracts away the complexities of data pipelines, model training, and computational scaling, delivering instead a seamless, user-friendly experience.

Example of the Magento MCP video:

Magento MCP Features

1. Natural Language to SQL

• Convert natural language questions into Magento specific SQL queries
• Execute SELECT and DESCRIBE queries safely
• No DDL and DML commands are allowed by default however you can change it
• Open chat in new window

2. Token Usage Analytics

• Real-time token usage tracking
• Cost(estimated) calculation based on model type
• Detailed statistics for:

- Current message tokens (prompt, completion, total)

- Session cumulative tokens

- Cost breakdown per request

- Total session cost

Support for different OpenAI models with respective pricing:

• GPT-3.5 Turbo
• GPT-4
• GPT-4 Turbo
• GPT-4 32k

3. Session Management

• Persistent conversation history
• Session-based context maintenance
• Automatic session cleanup
• Session ID tracking for debugging

4. Security Features

• API key configuration
• Query validation
• Safe SQL execution
• Session-based authentication

5. Error Handling

• Clear error messages
• Automatic error fixing suggestions
• SQL error analysis(can be send back to LLM to fix the issue)
• Table structure inspection

6. Architecture

• Decoupled OpenAI service for better maintainability
• Clean separation of concerns
• Extensible design
• Easy to customize and extend

Installation

Install the module using Composer:

composer require genaker/magento-mcp-ai

Enable the module:

bin/magento module:enable Genaker_MagentoMcpAi

Run setup upgrade:

bin/magento setup:upgrade

Clear cache:

bin/magento cache:clean

Configuration

1. API Keys

Navigate to Stores > Configuration > Genaker > Magento MCP AI

Enter your OpenAI API key

Save configuration

2. AI Rules

• Configure custom rules for the AI assistant
• Define query generation behavior
• Set response formatting rules

3. Documentation

• Add store-specific documentation
• Include table structures docs
• Document custom attributes and data models

4. Database Connection

Configure custom database connection in app/etc/env.php.

AI specific DB Connection name : ai_connection

you can add aditional read only connection or with user has read only prevelegy:

Database Configuration

Adding a Read-Only MySQL User

To create a read-only MySQL user for Magento, follow these steps:

Connect to MySQL as root:

mysql -u root -p

Create a new read-only user (replace username and password with your desired values):

CREATE USER ‘username’@’localhost’ IDENTIFIED BY ‘password’;

Grant read-only privileges to the Magento database (replace magento_db with your database name):

GRANT SELECT ON magento_db.* TO ‘username’@’localhost’;

For remote access (if needed), create the user with host ‘%’:

CREATE USER ‘username’@’%’ IDENTIFIED BY ‘password’;

GRANT SELECT ON magento_db.* TO ‘username’@’%’;

Flush privileges to apply changes:

FLUSH PRIVILEGES;

Verify the user’s privileges:

SHOW GRANTS FOR ‘username’@’localhost’;

Using the Read-Only User in env.php

Security Considerations

Always use strong passwords

Restrict access to specific IP addresses if possible

Regularly audit user privileges

Consider using SSL for remote connections

Monitor database access logs

Usage

1. Accessing the Assistant

Navigate to System > AI Assistant > MCP AI Assistant

Or use the direct URL: /admin/magentomcpai/chat/index

2. Making Queries

Type your question in natural language

The assistant will convert it to SQL

View results in the table below

Export results to CSV if needed

3. Managing Conversations

Use the “Clear” button to start a new conversation

Export chat history using “Save Chat”

Open chat in new window for better visibility

4. Monitoring Token Usage

View real-time token statistics in the expandable panel

Track costs for each interaction

Monitor cumulative session usage

See breakdown by:

Prompt tokens and cost

Completion tokens and cost

Total tokens and cost

Costs automatically calculated based on selected model

5. Error Handling

If a query fails, click “Fix in Chat”

The assistant will analyze the error

It may suggest checking table structures

Follow the suggested fixes

Architecture

1. OpenAI Service

The module now uses a dedicated OpenAI service class (OpenAiService) that:

Handles all API communication

Manages request formatting

Processes responses

Handles error cases

Provides consistent response format

Benefits:

Better separation of concerns

Easier to test and maintain

More flexible for customization

Cleaner code organization

Simplified error handling

2. Token Usage Tracking

The token tracking system:

Monitors API usage in real-time

Calculates costs based on current model

Maintains session statistics

Provides detailed usage breakdown

Supports all OpenAI model pricing tiers

Fine-Tuning the LLM

1. System Message Customization

The AI assistant uses a customizable system message to define its behavior. You can modify this in the admin configuration:

You are a SQL query generator for Magento 2 database. Your role is to assist with database queries while maintaining security. Rules:

1. Generate only SELECT or DESCRIBE queries
2. 2. Validate and explain each generated query
3. 3. Start responses with SQL in triple backticks: ```sql SELECT * FROM table; ```
4. 4. Reject any non-SELECT/DESCRIBE queries
5. 5. Maintain conversation context for better assistance
6. 6. Provide clear explanations of query results
7. 2. Custom Rules Configuration

Add your own rules in the admin configuration:

Navigate to Stores > Configuration > Genaker > Magento MCP AI

In the “AI Rules” field, add your custom rules

Each rule should be on a new line

Rules will override the default system message

Example custom rules:

• Always include table aliases in queries
• - Explain the purpose of each JOIN
• - Provide alternative query suggestions
• - Include performance considerations
• 3. Documentation Context

Add store-specific documentation to improve query accuracy:

Navigate to Stores > Configuration > Genaker > Magento MCP AI

In the “Documentation” field, add your store’s specific information

Include:

Table structures and relationships

Custom attributes and their usage

Business logic and rules

Common query patterns

Example documentation:

Table: sales_order

• Contains order information
• - Key fields: entity_id, increment_id, customer_id
• - Related tables: sales_order_item, sales_order_address

Custom Attributes:

• product_custom_type: string, values: ‘simple’, ‘configurable’, ‘bundle’
• - order_priority: integer, values: 1–5
• 4. Fine-Tuning Best Practices

a. Rule Structure

Be specific and clear in your rules

Use consistent formatting

Include examples where helpful

Prioritize security rules

b. Documentation Format

Use clear headings for each section

Include field types and constraints

Document relationships between tables

Add examples of common queries

c. Context Management

Keep documentation up to date

Review and update rules regularly

Monitor query performance

Adjust based on user feedback

d. Testing and Validation

Test new rules thoroughly

Validate query results

Check performance impact

Monitor error rates

Troubleshooting

1. API Key Problems

Verify API key in configuration

Check API key permissions

Ensure proper formatting

2. Query Errors

Use the “Fix in Chat” feature

Check table structures

Verify column names

Review SQL syntax

3. Performance Issues

Clear conversation history

Check database connection

Monitor API usage in the

Optimize queries

Support

For support, please contact:

Email: egorshitikov@gmail.com