MCP vs Skills: differences and when to use each

MCP connects an agent to external tools and data the moment it needs them. A skill gives the agent packaged instructions it loads into its own behavior before it acts. They solve different problems, and mixing them up gets you building infrastructure you don’t need, or asking a skill to do something it can’t.

If you’re starting from zero with these two terms, here’s the minimum you need to follow the rest of this post. MCP (Model Context Protocol) is an open protocol: an MCP server exposes a set of functions (tools) that an agent can call at runtime, similar to an API but designed for the model to discover on its own. I cover it in full in what MCP is. A skill, on the other hand, is a folder with a SKILL.md file: metadata plus markdown instructions the agent reads when a task matches what that skill describes. I define it in depth in what a skill is.

MCP vs Skills, side by side

	MCP	Skill
What it is	Client-server protocol that exposes tools, data, or prompts	Folder with a SKILL.md (instructions) and, optionally, scripts or templates
When it loads	On every call, at runtime	Metadata always visible; full content only when the task activates it
What it solves	Access to an external system that changes: a database, an API, a live service, a task queue	Getting the agent to follow a reusable procedure well, without re-explaining it every time
Context cost	One function call per use, plus its result	Nearly zero until it activates, then it loads its full content into context
Typical example	A server that checks the real status of an order in your database	A skill that knows how to generate a report in the exact format your team uses

The row that trips people up most is context cost. An MCP server with too many tools can flood your context window with function definitions the agent won’t even use for that task. A well-designed skill does the opposite: only its name and description stay in context by default, and the rest loads only when it’s needed. This is called progressive disclosure.

When to use each one

The question that actually matters isn’t “which one is better”. It’s: does the agent need to talk to something external that can change, or does it need to know how to do something it already knows how to do?

You need an MCP server when the agent has to read or write to a system that lives outside the conversation: your production database, a CRM, a payments service, the current state of a ticket. You can’t package that as a static instruction, because the data changes between one call and the next.

A skill is enough when what’s missing is the agent following a procedure with judgment: the exact format for your commits, or the steps for reviewing a pull request the way your team does it. None of that requires talking to a new external system. It’s knowledge about how to do something, not access to something.

And here’s the case almost nobody explains well: it’s common for the two to combine inside the same skill. A “close out the sprint” skill can include, in its SKILL.md, a step that says “use the get_open_tickets MCP tool to confirm nothing is left open before closing”. The skill supplies the judgment and the sequence; the MCP server supplies the real data at the moment it’s needed. A skill with no access to live data can only reason about what’s already in context, and an MCP server with nobody who knows when to use it is just a list of loose functions.

If you’re designing how an agent accesses tools and which pattern to reach for at each layer, the agentic patterns course covers this decision with more cases than fit in one post.

Frequently Asked Questions

Can I use MCP and Skills together in the same agent?

Yes, and it’s the most common setup in practice. The agent loads the skills relevant to the task, and when one of them needs external data, it calls an MCP tool right from there.

Can a skill replace an MCP server?

Not if you need data that changes. A skill can describe the perfect procedure for managing orders, but if it has no MCP tool connected to the orders system, it doesn’t know which ones are pending today. It can simulate the reasoning, not the real data.

Can an MCP server replace a skill?

You can technically stuff long instructions into an MCP tool’s description, but that’s not what it’s built for: an MCP tool describes a function that gets executed, not a multi-step procedure the agent needs to internalize. That’s what skills are for.

Where does a REST API fit into this comparison?

It doesn’t compete with either one directly. A REST API is what your own backend exposes; MCP is the protocol that lets an agent discover and call that API without you having to document it by hand in the prompt. If your real question is whether you should wrap your API in an MCP server, I cover that decision in MCP vs API: it’s a different problem from choosing between a skill and MCP.

Which one should I build first if I’m starting out?

If your agent already has all the data it needs in context and it’s just failing to follow a process well, start with a skill: it’s a folder with a SKILL.md, no infrastructure required. Build an MCP server when the real blocker is that the agent can’t see or touch something that lives outside the conversation.