customer-order-mcp-ai

# Storefront MCP Tool Enable AI-Assistant Experimental Printer Store MCP-SSE Enabled AI Assistant that support customer inquiries about product inventory, facilitates purchase transactions, and handles analytics questions. ## Solution Architecture  ## Features - Provide customer service through AI/Assistant with real-time access to product information and inventory levels, allowing for custom orders. - Recommend products based on customer preferences and available stock. - Use the MCP tool server for real-time interaction with microservices. - Check real-time inventory levels when answering product inquiries. - Facilitate product purchases by using product IDs and quantities. - Update inventory levels in real time after order fulfillment. - Offer ad-hoc analytics on order transactions through natural language queries. ## Use Case Samples ### Using CLI AI/Assistant in support  ### Using Web AI/Assistant in Web storefront  ## Environment Setup ``` ❯ node --version v22.14.0 ❯ npm --version 10.9.2 ❯ pnpm --version 10.6.5 ``` ## Setup LLM Provider ``` ❯ cat .env_example GROQ_API_KEY="Your GROQ_API_KEY" GROQ_API_URL="https://api.groq.com/openai/v1" > make a copy to file .env cp .env.examples .env > enter your own API key ``` repeat above step in MCP client and server folder ## Setup API Servers #### Run Microservices Products API (port 8082) ``` $ git clone https://github.com/minyang-chen/customer-order-mcp-ai.git $ cd backoffice-products-api $ npm install $ npm run dev ``` result log ``` customer-order-mcp-ai/backoffice-products-api on  main via  v22.14.0 ❯ npm run dev > products-api@1.0.0 dev > PORT=8082 tsx watch server.ts Printer Store Products API Server is running on port http://localhost:8082 /products ``` #### Run Microservices Order Fulfimment API (port 8081) ``` $ git clone https://github.com/minyang-chen/customer-order-mcp-ai.git $ cd backoffice-fulfillment-api $ npm install $ npm run dev ``` result log ``` ❯ npm run dev > fulfillment-api@1.0.0 dev > PORT=8081 tsx watch server.ts Printer Store Fulfillment API Server is running on port http://localhost:8081 /inventory /orders /purchase ``` ## Setup MCP Servers #### Run Order MCP Server (port 8083) ``` $ git clone https://github.com/minyang-chen/customer-order-mcp-ai.git $ cd mcp-order-server $ npm install $ npm run dev ``` result log ``` ❯ npm run start > apps@1.0.0 start > node order-sse-server.js Printer Store MCP SSE Server is running on http://localhost:8083/sse /sse /messages ``` ## Setup Assistant #### Run CLI AI/Assistant ``` $ git clone https://github.com/minyang-chen/customer-order-mcp-ai.git $ cd mcp-store-client/sse $ npm install $ npm run dev ``` result log ``` customer-order-mcp-ai/mcp-store-client/sse on  main is 📦 v1.0.0 via  v22.14.0 ❯ npm run client > sse@1.0.0 client > tsx client.ts https://api.groq.com/openai/v1 ================================================ Retrieving MCP Server available tools ================================================ MCP Tools: {{ ``` ## Technology Stack ``` LLM Provider - Groq (Qwen2.5) AI SDK by Vercel Nodejs / express for microservices ``` ## Contribution welcome any suggestions and improvement ideas.