Agent skills and MCP
The most interesting AI repositories this year are not models. They are skills, servers and tool layers that give an agent something to do. This guide explains the parts and why they matter.
In short
- A skill is a repeatable procedure an agent can run. A tool is a capability it can call. Both extend what the model can do on its own.
- MCP has become the default way for agents to reach outside themselves.
- Shared memory and context services decide whether a session has to start from zero.
What a skill is
A skill is a packaged procedure: a prompt, a checklist, a set of scripts and often reference material, stored so the agent can load it when a task matches. It is the difference between an agent that knows how to do something and one that improvises every time.
Tools and MCP
MCP, the Model Context Protocol, standardises how an agent discovers and calls tools. Instead of one custom integration per application, a server exposes capabilities that many agents can share. That is why the MCP ecosystem grew so quickly in 2026.
Skills marketplaces
Skill and plugin marketplaces for coding agents have grown into their own category, with plugins for Claude Code, Cursor, Codex, OpenCode and Copilot. The quality range is wide, so read what a skill actually does before installing it.
Memory and handoff
Long-term memory tools for coding agents let work be handed between vendors, so a session with one agent can be continued by another. It removes the most expensive part of agent work: re-explaining the context.
Recording intent
A newer idea is to record what you actually did on screen and turn it into a reusable skill automatically. It removes the main friction of authoring: writing the procedure by hand.
How to adopt them
Pick one workflow you do every week. Write a skill for it, connect only the tools it needs, and check the output yourself before automating further. Skills are a way to encode what you know, so they should start from real work, not from a general plan.
Last updated: October 2026.