DEV Community: Hari

#Day 1 - Learning MCP

Hari — Mon, 06 Apr 2026 03:06:02 +0000

I recently started learning MCP (Model Context Protocol), introduced by Anthropic, and it gave me a clear view of how AI actually works with real systems.

At a basic level, the flow is simple:

AI (inside a Host app) → MCP Client → MCP Server → Tools/Data.

The client acts as a bridge, the server exposes tools, and the host is where AI lives. Instead of guessing, AI can now fetch real data and perform actions.

It’s a small concept, but it opens the door to building real AI-powered systems.

MCP Server

Hari — Thu, 02 Apr 2026 17:49:14 +0000

Over the past few days, I’ve been diving deep into the Model Context Protocol (MCP), introduced by Anthropic, and it completely changed how I see AI systems.

Earlier, I thought AI was just about prompts. But MCP showed me something bigger — AI becomes truly powerful when it connects with real-world tools, data, and systems. Instead of guessing answers, it can fetch live data, run actions, and behave like an intelligent assistant.

What I learned is simple but powerful: AI is not just a brain, it needs hands. MCP gives those hands through tools and structured communication.

In this AI era, MCP-like architectures will shape how we build copilots, agents, and smart workflows. It’s not about smarter models alone, but better integration.

Going forward, I’m excited to build my own MCP servers and custom AI tools that solve real problems. This feels like the next step in becoming not just a developer, but an AI builder.

What I learned this month

Hari — Tue, 31 Mar 2026 17:55:19 +0000

Over the past month, I’ve been diving deep into Prompt Engineering, and it completely changed how I interact with AI.

I learned that Prompt Engineering is not just asking questions—it’s about giving clear context, defining roles, setting constraints, and guiding the AI toward the exact outcome you need. The quality of output depends heavily on how well you structure your input.

I explored techniques like breaking problems into steps, using examples, refining prompts iteratively, and thinking from the AI’s perspective. Small changes in wording can lead to big differences in results.

My biggest takeaway: Prompt Engineering is a skill. The better you communicate, the smarter the AI becomes.

Still learning, but excited about how this skill can improve productivity and problem-solving 🚀