Model Context Protocol (MCP)
Model Context Protocol (MCP) is an open standard that defines how AI assistants connect to external tools, data sources, and services. It provides a structured way for AI models to discover, understand, and use capabilities from any MCP-compatible server.
Explanation
MCP was created to solve a fundamental problem: AI assistants are powerful reasoners but have no built-in way to interact with external systems. Before MCP, every AI integration was a custom one-off — fragile, inconsistent, and locked to a single provider. MCP standardizes this connection layer with three primitives: Tools for actions, Resources for data, and Prompts for guided workflows. Think of MCP as USB for AI — a universal interface that lets any AI assistant plug into any service. The protocol supports both HTTP (for cloud deployments) and STDIO (for local tools) transports, with built-in authentication, capability negotiation, and session management. Any language that can speak HTTP can implement MCP, though TypeScript has the strongest ecosystem through frameworks like xmcp.
Related Terms
MCP Server
An MCP server is a service that implements the Model Context Protocol to expose tools, resources, and prompts to AI assistants. It handles connection management, capability negotiation, and request routing between AI clients and your underlying systems.
MCP Client
An MCP client is an AI assistant or application that connects to MCP servers to discover and use their capabilities. Popular MCP clients include Claude, Cursor, GitHub Copilot, and other AI-powered developer tools.
MCP Tools
MCP Tools are the action primitive in the Model Context Protocol. They let AI assistants perform operations — creating records, triggering deployments, sending messages, or any other action your service supports — by calling structured functions on your MCP server.
MCP Resources
MCP Resources expose read-only data to AI assistants. They let AI models query databases, read files, fetch configurations, or access any data from your system — without performing mutations or side effects.
MCP Prompts
MCP Prompts are guided workflows that an MCP server exposes to AI assistants. They define multi-step processes — like onboarding a new user, debugging an issue, or generating a report — that combine your tool's capabilities with structured AI guidance.
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