Think of MCP as a common plug for AI tools.
Direct answer
The Model Context Protocol (MCP) is an open standard that lets AI applications connect to external tools and data through a consistent interface. An AI client such as a coding assistant talks to MCP servers that expose things like files, databases or issue trackers. It reduces custom integrations, but you must manage permissions carefully.
How it fits together
| Part | Role |
|---|---|
| Client | the AI application that wants to use tools |
| Server | exposes tools or data |
| Tools and resources | actions and information the server offers |
Example uses
- Let an assistant search your project's documentation.
- Query a database in read-only mode.
- Create tickets in a project tracker.
Safety habits
- Use servers from sources you trust.
- Give the least access that works, such as read-only.
- Review what an agent plans to do before approving.
- Keep secrets out of prompts and logs.
Where Teyro fits
Teyro's Working with AI Coding Agents course turns this into short lessons you can play in a few minutes a day. It has 60 lessons, and you can start free.
The bottom line
MCP makes AI tools more useful and raises the importance of permissions.
