At its core, MCP (Model Context Protocol) is a way for us to enable AI agents to interact with other tools (on your computer or third-party services) in order to carry out tasks on our behalf. To understand what MCP is, we first need to understand how we used to connect systems together. In a previous video, we explained what an API (Application Programming Interface) is and how it allows software to “talk” to one another through a communication protocol that “translates” information from one system to another. This is how you can connect a language model like GPT or Claude to tools like Gmail, request information such as the contents of your emails, and get back a summary, for example. (By the way, if you haven’t watched it yet, now’s the time! ⏰) The key thing to remember is that this API was built specifically to handle that one particular task.
🧩 What Is MCP?
MCP (Model Context Protocol) is a new, open-source communication protocol invented by Anthropic (the company behind Claude). It was designed specifically to connect large language models (LLMs) or AI agents to data sources, services, and external tools such as development environments and systems.
Rather than requiring a custom connection every time a language model needs to interface with an external system (as is standard with APIs), MCP offers a unified standard that simplifies the process. It allows models to understand context, retrieve relevant information, and respond accurately and in a data-driven way — and crucially, it eliminates the need for developers to build a unique interface for every single tool.
Unlike an API, which requires a unique and separate connection for each data source, MCP acts as a “smart intermediary layer” that enables a language model to independently determine which data is relevant, access it in the right context, and incorporate it into the workflow. This removes the need for custom integrations for every system, allowing models to operate on up-to-date information in a consistent, secure, and context-aware manner.
ℹ️ Interestingly, this is similar to another protocol we all know: HTTP (HyperText Transfer Protocol), which allows our browser to communicate with websites. When we type a web address into the address bar, the browser sends a request for the site’s content (text, images, and files) to a remote server, receives the data, and displays it in the browser.
What Can You Do with MCP?
Let’s say, just as an example 😉, that my Downloads folder is an absolute mess. We all dump everything in there and rarely go back to tidy it up — it’s a tedious task that nobody wants to deal with. So why not use MCP to sort and organize it for us?
In the first step, we need to make sure we have the Claude desktop application installed and grant it access to folders on our computer. You can see exactly how to do that right 👈 here — it only requires very basic technical know-how. Once you’ve configured it, make sure to restart the application.
If you’ve done it correctly, when you open Claude and start a new conversation, you’ll see that a “Filesystem” option has been added to the Tool menu, as shown in the screenshot below 👇. Clicking on it lets you view and configure which actions can be performed on your folders — for example: reading a file, writing, creating folders, moving files between folders, and… you get the idea.
In the second step, all you need to do is write a prompt explaining to Claude what you want it to do. I asked it to go through all the files in my Downloads folder, categorize them by type, create a folder for each category, move all the relevant files into the appropriate folder, and delete any duplicates it finds. After Claude worked its magic, this is what it looked like 👇
What Business Applications Use MCP?
Imagine a small startup receiving dozens of résumés every week. The recruiting manager can’t keep up. Screening, summarizing, and sending emails becomes a daily burden. So the recruiter builds an assistant using MCP. The assistant accesses a file in Drive, summarizes the key information from each résumé, enters the data into a CRM, and sends a personalized email to each candidate — all without a single line of code and without any manual integrations. You simply describe what needs to happen, and the AI assistant takes care of it.
What’s the Difference? API vs. MCP
| Topic | API | MCP |
|---|---|---|
| What is it? | An interface that allows one system to call the functions of another | An open standard protocol that enables AI models to understand and access context from multiple systems |
| What is the goal? | To perform actions, retrieve or update data based on specific requests | To allow models to understand broad context from multiple data sources and act in a smart, context-aware way |
| How does it work? | Calls to functions (GET, POST, PUT, etc.) according to API definitions | Bidirectional connection between models and servers via a fixed protocol (MCP server + client) |
| Does it require customization per system? | Yes – every API is unique and requires a custom integration | No – MCP aims to create a unified standard that replaces custom integrations for each source |
| What is the emphasis? | A specific action based on a developer's request | Rich context, intelligent data retrieval, and transparent integration of models into existing tools |
| Who uses it? | Any developer who wants to connect systems together | Developers of AI applications, companies connecting models to internal knowledge sources |
Why Is MCP an Upgrade?
Because it doesn’t replace the API — it wraps it in a smart context layer. Instead of building custom connections for every data source, MCP lets you use a single protocol that understands how to access tools, interpret information, and integrate it seamlessly — essentially creating an intelligent system of specialized micro-experts.
This is a good moment to ask ourselves: what tools would you connect to your language model so it could handle tasks on your behalf and make your life easier?