Skills vs MCP Servers
Both extend what an agent can do. They solve different problems. Here’s how to pick.
What they actually are
A Skill
A folder with a SKILL.md file. Contains instructions, examples, templates, and optionally scripts. The agent reads it and follows the directions. No server, no API, no infrastructure.
Think of it as a playbook. The agent already has hands — the skill tells it what to do with them.
An MCP Server
A running process that exposes tools over the Model Context Protocol. The agent sends requests, the server executes them, and returns results. Requires code, a runtime, and usually some configuration.
Think of it as a new sense organ. The agent couldn’t do this before — now it can.
When to use which
| Situation | Use | Why |
|---|---|---|
| You want the agent to follow your team’s PR review process | Skill | It already knows how to read code and write comments. It just needs your specific checklist. |
| You want the agent to query your company’s internal database | MCP | It can’t access your database without a server providing that connection. |
| You want the agent to generate changelogs in a specific format | Skill | It already knows git. It just needs your format and conventions. |
| You want the agent to search Slack messages | MCP | It needs an authenticated connection to the Slack API. |
| You want the agent to create PPTX presentations | Skill | A skill can bundle a Python script that does the heavy lifting. No server needed. |
| You want the agent to manage Jira tickets | MCP | Needs live access to Jira’s API with your credentials. |
See the pattern? If the task requires live access to an external system, you need MCP. If the task requires domain knowledge or a specific process, you need a skill.
The quick test
Ask yourself two questions:
1. Could a smart person do this task with just a terminal, a text editor, and the right instructions?
Yes → Write a skill. No → You probably need MCP.
2. Does the task require authentication, a live API connection, or real-time data from an external service?
Yes → MCP. No → Skill.
Side-by-side comparison
| Skills | MCP Servers | |
|---|---|---|
| Format | Markdown + optional scripts | Running server process |
| Setup time | Minutes | Hours to days |
| Infrastructure | None — just files | Needs a runtime (Node, Python, etc.) |
| Portability | Works across 27+ agents | Works across MCP-compatible agents |
| External access | No (local files and tools only) | Yes (APIs, databases, services) |
| Security model | Sandboxed by the agent’s permissions | Server controls its own access |
| Best for | Workflows, conventions, templates | External integrations, data access |
They work best together
This isn’t either/or. The most effective setups use both. MCP gives the agent abilities. Skills teach the agent how to use those abilities well.
Without the MCP server, the agent can’t talk to Jira. Without the skill, it creates tickets that don’t follow your process. You need both.
Misconceptions
“Skills are just prompts.”
Skills can bundle scripts, reference files, templates, and assets. A PDF processing skill might include a Python script that does the actual extraction. The markdown tells the agent when and how to run it.
“MCP is always better because it’s more powerful.”
More powerful isn’t always better. Building an MCP server for something a skill handles in 20 lines of markdown is over-engineering. Skills are faster to write, easier to share, and work across more agents.
“Skills are going away now that MCP exists.”
The opposite. Skills adoption is accelerating. They solve a fundamentally different problem than MCP — teaching vs. connecting. Both are part of the agent ecosystem and both are actively supported by major platforms.