Melbis Shop

Official MCP server of Melbis Shop, a self-hosted e-commerce platform: an AI agent works in the store as an employee — files, database, catalogue, orders — under a staff login with per-command permissions.

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🛒 Melbis Shop — self-hosted e-commerce with an AI agent on staff

Melbis Shop is a self-hosted e-commerce platform: your server, your domain, your data. A native Windows back-office and a PHP storefront share one business logic, and the package ships an MCP server, so an AI agent — Claude Code, Codex, OpenCode, Goose, anything that speaks MCP — works in your store as an employee: under a staff login, with that person's permissions, every action signed by their name.

Built since 2002 for stores with real teams: several suppliers and price lists, hundreds to hundreds of thousands of products, staff who must not see each other's data.

🎯 Who it is for

A seller who has outgrown a marketplace and wants an own channel next to it — with a team of two to five people, suppliers' price lists and hundreds of SKUs. Not a page builder for a single product.

⚙️ Installation is automatic

You do not touch a console. In the Windows client you enter three things — the server's address, its root password and your domain — and the client installs everything over SSH itself: Docker, nginx, MySQL, PHP, the SSL certificate, the store. Updates run the same way, from the same window. A clean Ubuntu VPS becomes a working store in one sitting.

Seven steps with screenshots, from renting a server to the first task for the agent: https://melbis.com/en/doc/install/start/

🤖 What the AI agent does here

  • 66 MCP tools in the box: project files (modules, templates, statics, images — with version history), the database (pools of steps with locks and cache marks), catalogue trees, product files, storefront pages as a visitor sees them, the agent's memory and repository, the server over SSH, and the platform documentation itself.
  • 28 store tools with 285 commands come with the demo store: products and prices, descriptions, catalogue and attributes, suppliers, orders, scheduler tasks, users, image profiles, batch import of goods and files.
  • Permissions per command. Tools are data, not code: the owner grants each command to a person or a group. An employee with no database access still runs the agent — inside their own rights.
  • AI dispatcher. Store events — a new order, saved prices, a loaded price list — wake an agent under its own user: it works through them by its notes and sets tasks for people in the scheduler.
  • A real run, with the log and screenshots: one message in plain words → the first working version of a store — currencies, suppliers, a catalogue with 12 products, three roles with separate rights, a business-process roadmap — in 24 min 45 s and 21.2k tokens. Half an hour more: a redesign from a free third-party template. → https://melbis.com/en/doc/install/ai_work/

Connecting an MCP client

The MCP server (MelbisMCP.exe, stdio) is installed together with the Windows client — nothing to download separately. In the client open System → Connection → AI Assistant: the ready configuration is there with a Copy button for Goose, Cherry Studio and other MCP applications; Check Connection tests the licence, the login and the rights and says in words what is missing. Claude Code, Codex and OpenCode need no configuration at all — the client writes their settings into the store folder, open that folder as a project. The agent signs in under the person who runs it; there is no separate AI account, licence or password in the chat.

🚀 What makes the platform different

  • 🧮 One business logic for the storefront and the back-office: an order is calculated by the same code in the Windows app and on the site. Nothing to synchronise, nothing to diverge.
  • 🔐 Permissions down to the operation, the hour of the day and the server load, plus four independent access planes on every catalogue section — descriptions, prices, placement, browse. Content managers never see purchase prices.
  • 🔏 Sign-in by signature. The client derives a key from the password and signs every request; the server keeps only the public half, so the password never leaves the employee's computer.
  • ⚡ Batch back-office. Staff load a slice of the catalogue into a local database, edit it like a spreadsheet — bulk assignments, formulas per column — and push the changes in one packet. The storefront runs almost read-only.
  • 🧊 Five-level cache whose dependencies are collected automatically from the queries a module runs. Trick cache serves an older copy under a load spike; Smart cache refreshes ahead of expiry in a quiet moment.
  • 📦 Versioned orders, supplier locations with stock per location, tax rules on a territory tree, discount groups, customer groups with automatic loyalty rules, printed documents on FastReport.
  • 🛠️ A development environment inside the back-office: modules, templates and statics edited on the server with version history, SQL consoles, per-module cache settings, AI help in the editor with any OpenAI-compatible model and your own key.
  • 🧩 Storefront on your stack: the built-in PHP template engine, or Laravel on the same order logic — melbis/melbis-shop-laravel.
  • 🌍 Interface in 8 languages; storefront content translated by hand or automatically.

🖥️ What is under the hood

  • Server: Ubuntu with Docker — nginx, PHP 8.3 on Apache, MySQL 8.4, Certbot for SSL. Installed and updated by the client; the same setup.sh and update.sh live in this repository.
  • Client: a native Windows application with a local Firebird database per store.
  • AI agent: any MCP-capable application on the same Windows machine. The MCP server is part of the client package; no separate licence.

💰 Licensing

Free to install and run in demo mode. A licence is bound to a staff login, not to a computer, and starts at 1 € per day; monthly and yearly licences, full functionality in every plan: https://melbis.com/en/price/

🔗 Links

Your server. Your domain. Your AI partner.