Short answer
Use a skill when you want reusable instructions. Use an MCP server when you want live tools or external data. Many serious agent setups need both: a skill tells the model how to work, and an MCP server gives it the runtime capability to act.
Confusing the two leads to bad onboarding. Teams either expect a markdown bundle to behave like a tool integration, or they treat a live server as if it were just passive documentation.
Side-by-side comparison
| Question | Skill | MCP server |
|---|---|---|
| Primary purpose | Reusable instructions and workflows | Live tool access and external context |
| Runtime model | Loaded from files | Connected as a server process or remote endpoint |
| Best for | Review checklists, release playbooks, writing conventions | GitHub, browsers, databases, issue trackers, APIs |
| Common risk | Hidden scripts or over-broad instructions | Tool invocation against local files, secrets, and external services |
Why the best setups use both
A release engineering team might use a skill to define the checklist and approval flow for a release, and an MCP server to query GitHub, CI logs, or incident tooling while executing that playbook. The skill sharpens behavior. The MCP server provides live reach.
That layered model is also safer. You can review the guidance surface and the tool surface independently instead of hiding both inside one ambiguous bundle.
Why Aescut keeps the distinction explicit
Aescut records whether an entry is a plain skill, an MCP server, or a package that combines both. That matters because the review questions change. A skill review focuses on instructions, helper assets, and maintainer trust. An MCP review also asks what runtime tools exist, what auth it needs, and how much write power it has.
Sources and further reading
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