A brief introduction to HR AI: What is MCP?

Although many HRs have begun to use AI, most HRs are not from a technical background, so they often know the effects of AI but not the reasons behind them. In other words, they do not understand some of the technologies, principles and related terminology required to implement AI applications. 

If HR can understand some AI principles and terminology, they will be able to better communicate with technical experts and gradually understand not only how AI is applied, but also why it is applied.

This is why I am currently trying to popularize AI knowledge using simple language and examples.

Today I will explain in simple terms that HR can understand : What is the Model Context Protocol (MCP)?

You can think of it as:

"A set of speaking rules agreed upon between AI and external systems" is used to allow AI to remember contextual information such as context, roles, dialogue status, process position, etc.

Let’s use an HR scenario as an analogy:

Imagine you are an HR, and now an employee comes to ask you:

"Can I take three days off next week?"

Would you answer immediately? No!

You might first refer to:

• His leave record (see how much annual leave he has left)

• Are there any important company events next week?

• What impact will his leave of absence have on the business? Is there anyone who can temporarily take over his work during this period?

This background information is very important for you to answer questions. The same is true for AI!

So what is the use of “Model Context Protocol” in AI systems?

When you build a system like the "employee handbook Q&A robot", the AI ​​model itself does not know who is asking the question, what is being asked, which round of Q&A it is, or whether to jump to the system to check the data...

This is where the Model Context Protocol (MCP) comes in handy:

It's like:

?️ A  work record sheet + user profile + conversation log to help AI retain this information between each question and answer:

Here is an example of a quiz from the Employee Handbook:

Employee asked:

"I want to take annual leave, is that ok?"

An AI without MCP might answer:

“Annual leave can be applied through the OA system.”

(This is general talk, without considering the context)

The AI ​​with MCP will first check the context protocol and find:

• The employee is "Li Xiaoming" and works in the "Marketing Department"

• His annual leave totals 10 days. He has taken 8 days this year, leaving 2 days.

• The current process has not submitted the approval form

• He had just asked, "What is the process for vacation approval?"

So, the AI ​​will reply:

"You still have two days of annual leave this year. If you take three days off next week, you need to use up the remaining two days of annual leave first. You can apply for personal leave or adjusted leave for the remaining day, which will be approved by your supervisor. You can submit your application in the system and I can guide you."

✅ This shows the power of MCP!

To sum up in one sentence:

The Model Context Protocol (MCP)  is like equipping AI with an "employee profile + conversation record", allowing it to understand the context, have coherent conversations, and give targeted answers like a real HR .

If you are working on an intelligent question-and-answer system for employees and want AI to remember users, track conversations, and flexibly jump to other processes, then you must have a Model Context Protocol (MCP) behind it to make it  "smart and reliable . "