With the terms ‘skills’ and ‘MCP’ showing up in a lot of AI conversations, our team has been asked what the difference is between the two, and how people should be using them. Customers are creating skills to make their AI perform tasks a particular way, so it gets more accurate results consistently, and MCP (Model Context Protocol) is still a major driving force behind the conversations surrounding AI connectivity.

It’s easy to see why there’s confusion around the two terms. Both are ways of making your AI more powerful, and both are showing up in the same conversations, but the question shouldn’t be “skills vs. MCP.” It should be “what can I do with skills and MCP?” Let’s look at what each one does and why they work best together.

Skills vs. MCP

The relationship between skills and MCP is pretty simple. MCP allows AI to access data, while skills tell the AI how to perform a task. They work together to give your AI the right information and context to do the tasks efficiently.

Think of it like onboarding a new employee. MCP is the login credentials that get them into your systems. A skill is the training that shows them what to look for once they’re in, and how you want the results delivered. One without the other leaves you with a capable new hire who either can’t get to the information or doesn’t know what to do with it.

What is a Skill?

Both Claude and ChatGPT (on select plans) use “skills” to describe the specialized instructions you give your AI model so it can complete repetitive tasks more efficiently. Skills have been adopted by a growing number of AI platforms, and some tools offer similar functionality under other names, like custom instructions or templates. Though the name and implementation may change, the idea stays the same. When you create a skill, you’re giving your AI structured instructions on how to complete repeatable, specialized tasks.

You should use skills when:

  • There’s a consistent process for how something should be done.
  • There’s specialized knowledge your AI should know when answering questions.
  • There are specific guidelines or formats it should consider before it gives you an answer.

If you find yourself explaining the same thing to your AI over and over, that’s a sign you should be using a skill.

More Than a Prompt

You might be wondering how a skill is different from a well-written prompt, but skills go more in depth than prompts do. They have more structure and include metadata and extended documentation to provide more detailed instructions to your AI.

A prompt is typically something you write for one conversation, and a skill is something you can reuse across projects and conversations. You can even share the skills you create with other team members, so everyone gets more consistent, high-quality answers.

What is MCP?

MCP (Model Context Protocol) is a standard way to connect AI to external systems. A skill covers the “how,” and MCP covers the “what”. It lets your AI find out what tools are available, understand how your data is structured, and access the information it needs.

You should use MCP when:

  • You need access to data within external systems.
  • When you want your AI to run commands or execute specific actions (like sending emails or posting messages).
  • When you need real-time information, so your AI is working from live data.

Creating an MCP Server

When you decide you need an MCP server, your choices are to use a vendor’s MCP server, have one custom-built (which is expensive and takes a long time), or build your own. PopdockAI makes building your own easy with the MCP Server Composer. Build it without code, publish it in minutes, and stay in control of exactly what your AI can see and do.

Why Use Both Skills and MCP?

Skills and MCP work together to give your AI access to the tools it needs, while also giving instructions on how to use those tools effectively. With only MCP and no skills, your AI doesn’t know what to look for or how to return your data, so it has to figure it out on its own. With only skills and no MCP, your AI knows what it needs to do and the processes it should follow, but it doesn’t have access to your live business data. With both, they work together to give your AI the data access and context it needs to give you more thorough and consistent answers.

Try PopdockAI Free

You’re already investing in your AI architecture, so now is the time to try PopdockAI. Connect to all your systems, create the tools you need, give your AI full business context, and lock everything down with PopdockAI’s multi-layered security, all without code.

Start a 14-day free trial and experience how PopdockAI can help you create an AI architecture that actually scales.