What is MCP (Model Context Protocol)?
MCP, the Model Context Protocol, is an open standard for connecting AI assistants to tools and data: your files, databases, calendars, CRMs and other apps.
Before MCP, every AI app needed its own custom connection to every tool. MCP works more like a universal adapter: a tool that offers an MCP server can be used by any AI app that supports MCP.
What MCP means (and why it matters)
An AI assistant is far more useful when it can read your calendar, look up a customer or create a task. MCP standardises how those connections work, so tool makers build one MCP server and every compatible AI app can use it. That speeds up building AI agents that act in your business.
How MCP works
| Part | Role |
|---|---|
| MCP server | Offered by a tool or data source; lists the actions and data it provides |
| MCP client | Built into an AI app; connects to servers |
| Tools | Actions the AI can call, such as "create invoice" or "search contacts" |
| Resources | Data the AI can read, such as files or records |
| Permissions | What the user allows the AI to access and do |
The AI decides when to call a tool, much like tool use, but through a common standard.
MCP vs a regular API
| Regular API | MCP | |
|---|---|---|
| Built for | Developers writing code | AI apps discovering tools |
| Each new connection | Custom code each time | Plug in a server |
| Describes itself to the AI | No | Yes, lists its tools and inputs |
MCP servers are often built on top of a tool's existing API.
How to use MCP, step by step
1. Check what your AI app supports
Many AI assistants and developer tools can connect to MCP servers.
2. Find servers for the tools you use
Many software companies now publish official MCP servers.
3. Connect with the least access needed
Grant read-only access where you can, and only to the data the task needs.
4. Test on a real task
For example, "summarise this week's new leads from the CRM".
A worked example
An agency connects its AI assistant to its project tool and CRM through MCP. A manager asks, "Which clients have overdue tasks, and who is their contact?" The assistant queries both systems through their MCP servers and returns a short list, without anyone exporting spreadsheets.
Common mistakes
- Granting full access by default. Start read-only.
- Installing unknown servers. Use official or well-reviewed servers only.
- No audit. Review what each connection can do every few months.
FAQ
Who created MCP?
Anthropic introduced MCP in late 2024 as an open standard. Many companies and AI apps have since adopted it.
Do I need to code to use MCP?
Not to use existing servers in an AI app that supports them. Building your own server takes some development work.
Is MCP secure?
It is as secure as the access you grant. Use trusted servers, the least access needed, and review permissions.
Does MCP replace APIs?
No. It usually sits on top of APIs and makes them easy for AI apps to use.
Final verdict
MCP makes it much easier to connect AI to the systems your business already runs on. Use it to give assistants and agents useful, limited access, and they become far more practical.
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