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Comparison between competitors : ```html Caractéristics ClicShopping Shopify Magento WooCommerce IA Générative ✅ Natif multi-agents ❌ Apps tierces ❌ Extensions ❌ Plugins Support Multi-LLM ✅ 6+ fournisseurs ❌ OpenAI uniquement ❌ Limité ❌ Limité Base Vectorielle ✅ MariaDB native ❌ Externe requis ❌ Externe requis ❌ Externe requis Protocoles IA ✅ ACP/UCP/MCP ❌ Extensions ❌ Extensions ❌ Extensions WebSearch Intégré ✅ Natif ❌ Apps tierces ❌ Extensions ❌ Plugins Open Source ✅ GPL2/MIT ❌ Propriétaire ❌ Open Source ❌ Open Source Rag ✅ Semantic ❌ Propriétaire ❌ Open Source ❌ Open Source bi ✅ Analytic ❌ Propriétaire ❌ Open Source ❌ Open Source Agentic ✅ 8 Autonomous ❌ Propriétaire ❌ Open Source ❌ Open Source ```

ClicShopping strengthens its AI ecosystem through MCP compatibility with LmStudio ClicShopping announces its compatibility with LmStudio through MCP (Model Context Protocol). This integration allows users to select a chat directly within LmStudio and initiate a conversation with ClicShopping without accessing the ClicShopping interface. The integration simplifies the use of local AI models while maintaining centralized control. New features can be created easily, with all governance, business rules, and permissions fully managed by ClicShopping. LmStudio functions solely as a conversational access point, without duplicating application logic. An example image below illustrates a response generated by LmStudio in this integrated context. What is MCP? MCP (Model Context Protocol) is a standardized protocol that enables external applications to interact with structured services or models while delegating business logic, contextual data, and governance to a dedicated system. It enforces a clear separation between conversational interfaces and application backends. Why use MCP with ClicShopping? Direct access to ClicShopping capabilities from local AI environments such as LmStudio Centralized governance, security, and business logic managed by ClicShopping Rapid feature development without modifying AI client applications Reduced integration complexity and improved maintainability Support for advanced use cases combining e-commerce and conversational AI This compatibility example demonstrates ClicShopping’s strategy to build an open, interoperable AI ecosystem while retaining full control over its platform and governance model.

We are proud now to announce you ClicShoppingAI is a native agentic e-commerce platform built on an open, multi-agent architecture orchestrated by a central Orchestrator Agent. Designed for extensibility, the platform enables the dynamic addition of new agents and functional domains as business needs evolve. Multi-Agent Architecture At the core of the system, the Orchestrator Agent analyzes user intent and routes requests to the appropriate domain agents. Specialized agents operate across key functions: Semantic Agent for semantic search and content understanding using vector embeddings and retrieval-augmented generation (RAG). Analytics Agent for internal data analysis, automated SQL generation, and business intelligence. WebSearch Agent for retrieving external information from the public web and competitive sources. Hybrid Agent combining semantic, analytics, and web search capabilities to handle complex queries. Conversational Interface ClicShoppingAI features a conversational chat interface that supports natural language queries and delivers contextualized responses through intelligent intent analysis, contextual awareness, response validation, and multilingual support. Monitoring and Performance A centralized dashboard provides real-time visibility into platform activity with key performance indicators, including agent performance metrics, system latency, cache usage, alerts, trends, and token consumption statistics. Extensible by Design The platform relies on standardized interfaces and a clear three-layer architecture (Domains, Apps, Agents), ensuring clean separation between query processing, business logic, and autonomous agent behavior. This design allows rapid integration of new agents and domains without disrupting existing functionality. An example below : An request example across the chat :

ClicShopping Version 4.08 and more : MCP (Model Context Protocol) Documentation for ClicShopping Overview The ClicShopping MCP (Model Context Protocol) system allows for the integration of external Node.js or Python servers to extend the e-commerce application’s capabilities with advanced Artificial Intelligence functionalities. It provides a modular architecture for communication between ClicShopping and external services via standardized protocols. What is MCP? MCP is a communication protocol that enables applications to interact with language models and AI services in a standardized manner. In the context of ClicShopping, it facilitates: Bidirectional communication between the e-commerce application and external AI servers Integration of intelligent agents for task automation Data access via secured REST APIs Real-time monitoring and analytics of interactions Importance in E-commerce Advantages: Intelligent automation: Automatic order management, product recommendations 24/7 customer support: Smart chatbots for customer assistance Advanced analytics: Predictive analysis of sales and customer behavior Personalization: AI-based personalized recommendations Inventory optimization: Demand forecasting and automatic management Disadvantages: Implementation complexity: Requires advanced technical skills Infrastructure costs: External servers and AI services External dependency: Risk of third-party service outages Security: Management of tokens and secure access Examples of potential implementations: 🔗 Social Media Integrations Instagram Shopping: Automatic product synchronization with Instagram posts Facebook Marketplace: Automatic publication of new products TikTok Shop: Integration with TikTok trends for recommendations Pinterest: Automatic creation of pins for popular products 🏢 ERP Integrations SAP: Synchronization of stocks, orders, and customers Oracle NetSuite: Accounting integration and financial management Microsoft Dynamics: Synchronization of customer and sales data Odoo: Full CRM/ERP integration with inventory management 📈 Marketing Integrations Mailchimp: Automatic customer segmentation and targeted campaigns HubSpot: Lead scoring and customer journey automation Google Analytics 4: Advanced tracking of conversions and behavior Facebook Ads: Automatic optimization of advertising campaigns 💳 Payment Integrations Stripe: Management of subscriptions and recurring payments PayPal: Integration of payments and refunds Klarna: Installment payments and credit scoring Apple Pay/Google Pay: Optimized mobile payments 📦 Logistics Integrations DHL/UPS/FedEx: Automatic shipping cost calculation and tracking Amazon FBA: Amazon stock management and synchronization Shopify Fulfillment: Optimization of distribution centers ShipStation: Multi-carrier shipping automation 🎯 Analytics & BI Integrations Tableau: Advanced sales dashboards Power BI: Predictive analytics and automated reports Google Data Studio: Marketing and performance reporting Mixpanel: Advanced user event tracking 🤖 AI & Chatbot Integrations OpenAI GPT: Smart chatbot for customer support Dialogflow: Multilingual conversation management Zendesk: Automation of support tickets Intercom: Real-time chat with lead qualification 📱 Mobile Integrations React Native: Native mobile application Flutter: Cross-platform iOS/Android app PWA: Progressive Web Application Push Notifications: Personalized notifications 🔐 Security Integrations Auth0: Advanced authentication and authorization Okta: Identity and access management Cloudflare: DDoS protection and CDN Sentry: Real-time error monitoring Examples of Integration Code Example 1: Instagram Shopping Integration // New MCP endpoint for Instagram class InstagramIntegration extends \ClicShopping\OM\PagesAbstract { public function syncProductsToInstagram(): void { $products = $this->getProductsForSync(); foreach ($products as $product) { $instagramData = [ 'name' => $product['products_name'], 'description' => $product['products_description'], 'price' => $product['products_price'], 'image_url' => $product['products_image'], 'availability' => $product['products_quantity'] > 0 ? 'in stock' : 'out of stock' ]; $this->postToInstagramAPI($instagramData); } } } Example 2: SAP ERP Integration // Synchronization with SAP via MCP class SAPIntegration extends \ClicShopping\OM\PagesAbstract { public function syncOrdersToSAP(): void { $orders = $this->getPendingOrders(); foreach ($orders as $order) { $sapData = [ 'order_number' => $order['orders_id'], 'customer_code' => $order['customers_id'], 'order_date' => $order['date_purchased'], 'items' => $this->formatOrderItems($order['items']) ]; $response = $this->sendToSAP($sapData); $this->updateOrderStatus($order['orders_id'], $response['status']); } } } Example 3: AI Chatbot with OpenAI // Smart chatbot for customer support class AIChatbot extends \ClicShopping\OM\PagesAbstract { public function handleCustomerInquiry(string $message): array { $context = $this->getCustomerContext(); $prompt = "As an e-commerce assistant, help this customer: " . $message; $prompt .= "\nCustomer context: " . json_encode($context); $response = $this->callOpenAI($prompt); // If necessary, create a support ticket if ($this->requiresHumanIntervention($response)) { $this->createSupportTicket($message, $context); } return [ 'response' => $response, 'requires_human' => $this->requiresHumanIntervention($response), 'suggested_products' => $this->extractProductSuggestions($response) ]; } } Example 4: Predictive Analytics // Sales prediction with AI class PredictiveAnalytics extends \ClicShopping\OM\PagesAbstract { public function predictSales(): array { $historicalData = $this->getSalesHistory(); $externalFactors = $this->getExternalData(); // Weather, events, etc. $prediction = $this->runMLModel([ 'historical_sales' => $historicalData, 'seasonality' => $this->getSeasonalityFactors(), 'external_factors' => $externalFactors, 'inventory_levels' => $this->getCurrentInventory() ]); return [ 'predicted_sales' => $prediction['sales'], 'recommended_stock' => $prediction['stock_recommendations'], 'confidence_score' => $prediction['confidence'], 'risk_factors' => $prediction['risks'] ]; } } Concrete Use Cases 🛒 B2C E-commerce Personalized recommendations: “Customers who bought this product also viewed…” 24/7 chat support: Automatic assistance with escalation to a human Intelligent inventory management: Stock-out prediction Dynamic pricing: Automatic price adjustment based on competition 🏢 B2B E-commerce Personalized catalog: Prices and products according to the customer Large order management: ERP integration for high volumes Automated reporting: Dashboards for resellers Discount management: Automatic calculation based on commercial agreements 🎯 Marketplace Multi-vendor synchronization: Centralized stock management Fraud detection: Automatic detection of suspicious transactions Fee optimization: Automatic commission calculation Dispute management: Automation of resolution processes 📱 Mobile Commerce Smart push notifications: Personalized notifications Geolocation: Location-based offers Mobile payments: Apple Pay/Google Pay integration Image recognition: Product search by photo Measurable Business Benefits 📈 Sales Performance +25% conversion thanks to personalized recommendations -40% shopping cart abandonment with the smart chat +30% average cart value via cross-sell suggestions -60% order processing time with automation 💰 Cost Optimization -50% support costs with chat automation -30% logistics costs with inventory optimization -25% marketing costs with precise targeting -70% human errors with process automation 🎯 Customer Experience +90% customer satisfaction with 24/7 support -80% response time to customer inquiries +45% loyalty thanks to personalization +60% problem resolution rate on first interaction MCP Architecture General Architecture ┌─────────────────┐ ┌─────────────────┐ ┌─────────────────┐ │ ClicShopping │◄──►│ MCP Server │◄──►│ AI Services │ │ (PHP Core) │ │ (Node.js/Python)│ │ (OpenAI, etc.)│ └─────────────────┘ └─────────────────┘ └─────────────────┘ │ │ │ ▼ ▼ ▼ ┌─────────────────┐ ┌─────────────────┐ ┌─────────────────┐ │ Database │ │ Monitoring │ │ Analytics │ │ │ │ & Logs │ │ & Reports │ └─────────────────┘ └─────────────────┘ └─────────────────┘ ClicShopping MCP Architecture The ClicShopping MCP system is organized into several components: 1. Core Classes MCPConnector: Connection and protocol management McpMonitor: Performance oversight and monitoring McpService: Core services for MCP operations McpDecisionAgent: Intelligent agent for automation 2. API Endpoints /mcp&customersProducts: Products API /mcp&ragBI: RAG (Retrieval-Augmented Generation) Interface for admins - the rag must ve activated You are free to create other EndPoints (see example above) 3. Admin Configuration Administration interface for configuring MCP servers Token, port, SSL management Real-time monitoring What is Not Provided with the APP The Chat The chat interface is not included in the ClicShopping application. To implement it: Chat construction and connection: Create a chat interface (HTML/CSS/JavaScript) Connect to the MCP server via WebSocket or HTTP Use the available API endpoints: // Example of chat connection const chatEndpoint = 'http://your-domain/index.php?mcp&customersProducts'; // Sending a message fetch(chatEndpoint, { method: 'POST', headers: { 'Content-Type': 'application/json', 'Authorization': 'Bearer ' + token }, body: JSON.stringify({ message: 'Looking for products', context: { user_type: 'client', session_id: 'unique_session_id' } }) }); The Node.js/Python MCP Server The external MCP server is not provided with the application. To build it: Node.js MCP Server Example: // Example of a Node.js MCP server const express = require('express'); const app = express(); app.post('/mcp/products', async (req, res) => { // Logic for processing product requests const response = await processProductRequest(req.body); res.json(response); }); app.listen(3000, () => { console.log('MCP server started on port 3000'); }); Server Connection: Configuration in the ClicShopping admin: Host, Port, SSL, Token API Usage: Access via the /Shop/json routes Configuration and Usage Configuration in the Administration MCP configuration is done directly in the ClicShopping administration interface: Available parameters: Server Host: Address of the MCP server (default: localhost) Server Port: Port of the MCP server (default: 3000) SSL: Secure protocol activation Token: Authentication token for security Status: MCP module activation/deactivation Alert configuration: Latency thresholds: Maximum response time Availability thresholds: Maximum downtime Notifications: Email alert configuration Access API - Shop Routes The MCP API is accessible via the /Shop/json routes of ClicShopping: 1. CustomersProducts.php This class serves as the main entry point for the MCP products API. It manages: Main features: Product list: GET ?mcp&customersProducts&action=products Product detail: GET ?mcp&customersProducts&action=product&id={ID} Search: GET ?mcp&customersProducts&action=search&query={TERM} Statistics: GET ?mcp&customersProducts&action=stats Categories: GET ?mcp&customersProducts&action=categories Recommendations: GET ?mcp&customersProducts&action=recommendations Customer chat: POST ?mcp&customersProducts (with JSON body) Example usage: # Product list curl "http://localhost/clicshopping_test/index.php?mcp&customersProducts&action=products&limit=5" # Product search curl "http://localhost/clicshopping_test/index.php?mcp&customersProducts&action=search&query=washcloth" # Customer chat (POST) curl -X POST "http://localhost/clicshopping_test/index.php?mcp&customersProducts" \ -H "Content-Type: application/json" \ -d '{"message": "I am looking for cleaning products", "context": {"user_type": "client"}}' 2. RagBI.php RAG (Retrieval-Augmented Generation) interface identical to ClicShopping’s internal chat but accessible via MCP: To use it, you must activate the Agent RAG-BI inside the administration. Features: Semantic queries: Smart search in the database Analytical queries: Analysis of sales and performance data OpenAI Integration: Use of language models for responses Translation cache: Performance optimization Example usage: # RAG BI Query curl -X POST "http://localhost/clicshopping_test/index.php?mcp&ragBI" \ -H "Content-Type: application/json" \ -d '{"message": "Give me a table of the evolution of turnover by month for the year 2025"}' 3. customerOrders.php Customer order management API: Features: Order list: GET ?mcp&customerOrders&action=list_orders&customer_id={ID} Order detail: GET ?mcp&customerOrders&action=read_order&order_id={ID} Cancellation: POST ?mcp&customerOrders&action=cancel_order Messages: POST ?mcp&customerOrders&action=send_message History: GET ?mcp&customerOrders&action=history&order_id={ID} Examples of Future Implementation Agentic Approach The MCP system supports the implementation of intelligent agents for: Recommendation Agent: // Example of a Recommendation Agent class RecommendationAgent { public function analyzeCustomerBehavior($customerId) { // Analyze customer behavior // Generate personalized recommendations } } Stock Management Agent: // Example of a Stock Management Agent class StockAgent { public function predictDemand($productId) { // Demand prediction // Optimization of stock levels } } Customer Support Agent: // Example of a Support Agent class SupportAgent { public function handleCustomerInquiry($message) { // Process customer inquiries // Automatic escalation if necessary } } Monitoring and CronJobs Monitoring System The MCP system includes complete monitoring: Monitored metrics: Response time: Latency of MCP requests Availability: Uptime of the MCP server Errors: Error rate and error types Security: Intrusion attempts and unauthorized access Automatic alerts: Performance thresholds: Alerts if response time > threshold Service outages: Notifications in case of unavailability Suspicious activities: Detection of attacks or abuse CronJob Configuration The MCP system uses scheduled tasks for: 1. Health Monitoring (every 5 minutes) // CronJob: McpHealthCron // Checks the health of the MCP server // Stores alerts in the database // Cleans up old alerts (>30 days) 2. Decision Agent (every 5 minutes) // CronJob: mcp_agent // Executes the intelligent decision agent // Processes automated tasks // Updates recommendations CronJob Configuration: # Add to crontab */5 * * * * /usr/bin/php /path/to/clicshopping/index.php?cronId={CRON_ID} Security Authentication and Authorization Access Tokens: Secure generation: Unique tokens per session Automatic expiration: Token rotation Validation: Verification on every request Endpoint protection: Configured CORS: Controlled access by origin Parameter validation: Input sanitization Production mode: Access restrictions in production Security Best Practices Use HTTPS in production Configure strong tokens and renew them regularly Limit access by IP if necessary Monitor logs to detect suspicious activities Regularly update dependencies Troubleshooting Common Problems 1. Connection to the MCP server fails Check the configuration (host, port, SSL) Verify that the MCP server is started Check error logs 2. Authentication errors Verify the token validity Check permission configuration Check security logs 3. Degraded performance Check monitoring metrics Optimize database queries Increase resource limits Logs and Debugging Log files: MCP Logs: Available in the database and admin interface (export) for various traceability PHP Error Logs: Standard PHP configuration Monitoring Logs: mcp_alerts database Support and Resources Additional Documentation DeepWiki/ClicShopping: Detailed architecture : https://deepwiki.com/ClicShopping/ClicShopping GitHub Issues: Technical support and bugs : https://github.com/ClicShopping/ClicShopping/issues ClicShopping Forum: Community and assistance

This version move the includes directory to Core directory. If you install an app do not forget to change the includes directory into Core directory. Until the transition is not completed, please do not install directly from the ClicShopping AI an App. Download and do it manually. Thank you.