Introduction: A New Way to Work with AI

What if your AI assistant could do exactly what you need it to—like count words in a sentence, fetch live data, or even control smart devices—without waiting for the developers to add those features? That’s where the Model Context Protocol (MCP) comes in. It’s a powerful new framework from Anthropic that lets you extend AI models like Claude with custom tools you build yourself. In this blog, I’ll break down the concept of MCP, share how I used it to create a simple word-counting tool for Claude Desktop, and explore why this technology is so exciting for the future of AI.

What is MCP? A Bridge Between AI and Your Ideas

The Model Context Protocol, or MCP, is like a universal translator that lets AI models (like Claude) talk to external tools you create. Imagine Claude as a super-smart assistant who can follow instructions—but only knows what’s built into it. MCP acts as a bridge, allowing Claude to send requests to your custom tool (say, a word counter) and get answers back, all in a standardized way.

Here’s the basic idea:

• Claude (the AI) sends a message saying, “Hey, can you do this task for me?”
• Your Tool (the server) listens for that message, does the work, and sends the result back.
• The Communication happens through a simple format called JSON-RPC, using basic input/output channels (like a terminal’s input and output).

For example, I wanted Claude to count words in a sentence. With MCP, I built a small server that listens for Claude’s request, counts the words, and tells Claude the answer—like, “The text has 5 words.” It’s that straightforward!

Why MCP is a Big Deal

So, why should you care about MCP? Here are a few reasons it’s a game-changer:

• Make AI Your Own: You’re no longer stuck with what Claude can do out of the box. Want it to analyze your local files? Check stock prices? Turn on your smart lights? With MCP, you can make it happen by writing your own tools.
• Works with Any Language: Whether you prefer Python, JavaScript, or another language, MCP doesn’t care—it’s designed to be flexible.
• Endless Possibilities: From simple tasks like my word counter to complex integrations (think connecting to APIs or databases), MCP lets you dream big.

When I got MCP working with Claude Desktop, I was amazed at how easy it was to teach Claude something new. I just told it, “Count the words in: hello world,” and it responded, “The text has 2 words.” That moment felt like magic—it showed me how MCP can turn AI into a truly personal assistant.

How Does MCP Work? The Big Picture

At a high level, MCP connects Claude to your tool in three main steps:

1. The Handshake: When your tool starts, Claude sends a message called initialize to say hello and ask what your tool can do. Your tool responds by listing its capabilities—like, “I can count words.”
2. The Request: When you ask Claude to do something (e.g., “Count the words in this sentence”), it sends a message to your tool with the task details.
3. The Response: Your tool processes the request, does the work (like counting words), and sends the answer back to Claude, which then shares it with you.

This all happens behind the scenes, so to you, it just looks like Claude suddenly gained a new skill. In my case, I set up a Python-based server for Claude Desktop, and once it was running, Claude could count words as if it were a built-in feature.

My Journey: Building a Word Counter with MCP

To see MCP in action, I decided to build a simple word-counting tool for Claude Desktop. The idea was straightforward: I’d ask Claude to count the words in a sentence, and my tool would do the work. Here’s what I learned from the experience:

• It’s Empowering: Teaching Claude to count words felt like giving it a superpower. Suddenly, I could imagine all sorts of other tools I could build.
• It’s Accessible: You don’t need to be a coding expert to get started. I used Python because it’s beginner-friendly, but the concept is the same no matter what language you choose.
• It’s Fun: There’s something thrilling about seeing Claude use your tool for the first time. When I typed “Count the words in: hello world” and got “The text has 2 words” back, I couldn’t stop smiling.

What’s Next for MCP? Imagine the Possibilities

My word counter is just a starting point. MCP opens the door to so many exciting ideas:

• Productivity Boosters: Build a tool to summarize your local documents or fetch your calendar events.
• Creative Helpers: Create a tool that generates random writing prompts or analyzes the tone of your text.
• Smart Integrations: Connect Claude to live data—like weather updates or stock prices—or even control smart home devices.

The best part? MCP isn’t just for one person. Developers can share their tools with the community, creating a library of features anyone can add to Claude. Imagine downloading a “weather reporter” tool or a “code debugger” tool with a single click—that’s the future MCP could enable.

Conclusion: Join the MCP Revolution

The Model Context Protocol is more than just a tech concept—it’s a way to make AI truly yours. By building a simple word-counting tool for Claude Desktop, I got a glimpse of how MCP can transform the way we interact with AI. It’s easy to get started, incredibly powerful, and opens up a world of creativity.

If you’re curious to try MCP yourself, Anthropic’s MCP Quickstart Guide is a great place to begin. Whether you’re a developer or just someone who loves tinkering with tech, MCP lets you take AI to the next level. What will you build for Claude? I’d love to hear your ideas—drop them in the comments below!