AI Glossary · Last reviewed August 2026

MCP

· Model Context Protocol

Hand-written by a real person. Reviewed against current practice in August 2026.

Definition

An open standard that lets AI models connect to external tools, data sources and services in a consistent way.

Why it matters

MCP (Model Context Protocol) is an emerging standard that lets AI models connect to external tools, databases, and services in a standardized way. Instead of each AI tool building custom integrations, MCP provides a universal plug-and-play system.

As MCP adoption grows, AI tools that support it will be able to access more data sources and perform more actions, making them significantly more useful.

How it works

4 steps

STEP 01

Server exposes capabilities

An MCP server declares what tools, data sources, and actions it can provide - like read email or search database.

STEP 02

Client discovers tools

The AI model's client connects to the MCP server and learns what tools are available.

STEP 03

Model calls tools as needed

During a conversation, the model decides which tools to use and sends structured requests through the MCP protocol.

STEP 04

Results flow back

The tool executes the action and returns results to the model, which incorporates them into its response.

Frequently asked questions

What is MCP in AI?+

MCP (Model Context Protocol) is a standard that allows AI models to securely connect with external tools, data sources, and applications.

Why is MCP important for AI agents?+

MCP helps AI agents access external information and tools in a consistent and controlled way.

How does MCP improve AI workflows?+

It makes integrations easier by providing a common protocol for connecting AI systems with external services.

New to MCP?

See the tools that use it.

The fastest way to understand MCP is to see it inside real products. Browse hand-reviewed tools that put it to work, each one checked by a person before it was listed.

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