If you’ve been reading about AI tools lately, you may have come across the term “MCP” — Model Context Protocol. It’s becoming one of the most important pieces of infrastructure in AI right now, even though most people have never heard of it. Here’s what it actually is, in plain terms.
The problem MCP solves
AI models like ChatGPT or Claude are very good at reasoning, writing, and answering questions — but on their own, they can’t actually do anything outside the conversation. They can’t check your calendar, look up an order in your store, or update a page on your website. To make that possible, someone has to build a custom connection between the AI and each individual tool.
Before MCP, that meant a lot of duplicated work. If a company wanted its AI assistant to work with Gmail, Slack, and a CRM, developers had to build three separate, custom integrations — each with its own quirks, its own authentication method, and its own maintenance burden. Multiply that across every AI tool and every app a business uses, and the number of one-off integrations needed becomes unmanageable.
What MCP actually is
MCP is an open standard, introduced by Anthropic in late 2024, that defines a common way for AI models to connect to external tools and data sources. Instead of every AI-to-app connection being built from scratch, an app exposes an “MCP server” — a standardized interface describing what it can do — and any AI system that understands MCP can connect to it the same way.
A simple way to think about it: MCP is to AI tools what USB is to hardware. Before USB, every device needed its own specific port and cable. USB gave every device a common connector, so any USB device could plug into any USB port. MCP does the same thing for software — any MCP-compatible AI can plug into any MCP-compatible app, without custom-built wiring in between.
What this looks like in practice
Once an app has an MCP server, an AI assistant connected to it can genuinely take action, not just talk about it. A few real examples:
- WordPress — an AI can create draft posts, update SEO metadata, manage pages, and organise content directly inside your site
- Shopify — an AI can look up orders, check inventory, create discounts, or update product listings
- Google Calendar / Gmail — an AI can check your schedule, draft emails, or create calendar events
- Design and project tools — an AI can pull design specs from Figma, or read project data from tools like Asana or Jira
Rather than copying information back and forth between an AI chat window and each of these tools manually, MCP lets the AI work inside them directly, on your behalf.
Why it’s a big deal
MCP turns AI assistants from something you talk to into something you can actually delegate work to. A few reasons this matters:
- Any app becomes AI-ready. A company only needs to build one MCP server, and it instantly becomes usable by every MCP-compatible AI, not just one vendor’s chatbot.
- It’s an open standard, not a walled garden. Because MCP is open, it’s being adopted broadly across the AI industry, rather than locking businesses into one company’s proprietary integration system.
- It reduces engineering overhead. Businesses no longer need custom-built integration code for every AI-to-app connection — the protocol handles the common plumbing.
- It’s the backbone of “agentic AI.” The current shift toward AI agents that can complete multi-step tasks on their own — not just answer questions — depends on the AI being able to reliably connect to and act inside real tools. MCP is a big part of what makes that reliable.
What it means for your business
If your business runs on WordPress, WooCommerce, Shopify, or similar platforms, MCP is quietly changing what’s possible with AI on top of them. It’s the same underlying technology that lets an AI chatbot on your website pull real product data from your store, or lets an AI assistant draft and publish content directly to your WordPress site rather than just handing you text to copy and paste.
As more of the tools businesses already use add MCP support, the practical result is AI that can genuinely get things done inside your existing systems — not just talk about them.
Curious how MCP-powered AI tools could work inside your own website or store? Get in touch with the Webbit team — we build and manage exactly this kind of AI integration for WordPress and Shopify businesses in Malaysia.
