Why MCP Protocol Is the Next Essential Skill for AI Developers

Hello, I’m Jianghu with ten years of experience.

I've recently published two articles on MCP because my current project uses it, and I want to share my insights.

NOTE: This is the last MCP article for now; the next piece will cover Go 1.23 iterators.

By mid‑2025, the once‑hot MCP protocol has cooled but become the factual standard, akin to HTTP for browsers.

I consider MCP a must‑learn skill for all developers, comparable to HTTP.

Some claim 2025 is the Agent era, and MCP has been pivotal by unifying models with external data, just as HTTP unified browsers and servers.

Historically, tool use distinguished humans from animals; similarly, agents are intelligent because they use tools.

Within six months, the MCP website released three major versions.

The rise of large models has accelerated technological change, presenting both opportunities and challenges for developers.

In the AI era, learning new technologies efficiently is crucial.

Using models like DeepSeek or ChatGPT can aid learning, but only for well‑known technologies that the models have been trained on; newer topics like MCP lack sufficient data, leading to unreliable outputs.

Therefore, I spent considerable time reading the official MCP documentation, which remains the most authoritative source.

However, for busy developers, reading raw docs can be inefficient.

I recommend beginners start with curated columns or books, which provide interaction and fewer errors.

I’ve read two MCP books: “MCP Development from Beginner to Practice” and “MCP Minimalist Development: Building Efficient Agents” . Both complemented the official docs and would have saved time if read earlier.

The first book starts with fundamentals and reinforces concepts through practice, suitable for newcomers with some AI background.

The second book also covers MCP basics but extends into Agent concepts, offering a more comprehensive, hands‑on approach.

Understanding MCP’s history—from its origins to its current ecosystem and future—helps grasp its full context.

Learning steps: study MCP’s history, explore major platforms in its ecosystem, develop an MCP service, then build an Agent to apply MCP in practice.

For deep mastery, reading the official docs and SDK source code remains essential.

Suggested learning order: start with a beginner‑friendly book for quick onboarding, then practice, and finally consult official documentation for advanced details and updates.

What resources have you used to learn MCP? Share in the comments.

Hope this article inspires you.