Definition
An MCP server is a program that exposes tools, data, or prompts to an AI agent over the Model Context Protocol, a shared standard for connecting agents to external systems.
In practice
Before a shared protocol, every agent framework defined tools its own way, so an integration written for one runtime was worthless to another. MCP makes the connection reusable: write a server once and any MCP-capable agent can call it. In practice an MCP server is how an agent reaches a database, an internal API, or a third-party service without that integration being baked into the runtime. The security consequence is worth stating plainly, because it is easy to miss: connecting an MCP server grants the agent whatever that server can do, so scope its credentials to the job rather than to convenience.
Example
A company keeps its order history in an internal database. Rather than pasting exports into prompts, it runs a small MCP server that exposes two tools: look up an order by number, and list the orders for a customer. Any MCP-capable agent can now answer order questions. The server's database credential is read-only, so even a confused agent can look orders up but cannot change or delete a single one.
Common questions about MCP server
What does an MCP server give an AI agent?
An MCP server gives an agent tools, data, or prompts over the Model Context Protocol, so the agent can reach a database, an internal API, or a third-party service without that integration being built into its runtime. Written once, the same MCP server works with any agent that speaks the protocol.
Is connecting an MCP server safe?
Connecting an MCP server grants the agent everything that server can do, so safety depends on the server's own credentials and scope. Give each MCP server the narrowest access the job needs, such as read-only where the job only reads, and review a new server like any other integration before trusting it.
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