What it is
The Model Context Protocol, or MCP, is an open standard introduced by Anthropic for connecting AI applications to outside tools and data. An MCP server exposes tools, resources and prompts in a common format. An MCP client, such as Claude Code or the Claude desktop app, connects to it and offers those tools to the model, so one integration works with any client that speaks the protocol.
Servers can run locally and talk over standard input and output, or run remotely over HTTP. Typical servers wrap a database, a browser, a file system or a company's internal API. Because the client decides which servers are connected and what each may do, MCP is also where a team sets the limits on what an agent can reach.
How I use it
- Part of the agent setup I build my products with, alongside Claude Code and purpose-built subagents.
- I treat each connection as a permission decision: what an agent can read, what it can change, and what it must ask about first.
- Agents that look at data are built to return findings, not dump rows into a conversation.
MCP is the right tool when an agent needs a specific system, like a database or a browser, and the same connection should work across tools. It is part of my agent toolkit next to Claude Code. The part I care about is the boundary: each connection decides what an agent is allowed to touch, and that decision is mine, not the agent's.
Questions
What is MCP used for?
It gives an AI agent a standard way to reach tools and data, like a database, a browser or an internal API, so one integration works across every client that supports the protocol.
Is it safe to connect an AI agent to company systems?
It can be, if each connection is scoped. I decide what an agent may read and change, and agents that query data return findings rather than raw records.