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What is MCP? The Universal Connector for AI

The Model Context Protocol is an open standard that gives AI models a universal way to connect to any data source or tool. Understand the problem it solves and how it works.

MCP Architecture

The universal connector between AI models and any data source

Before MCP: N×M Problem

5 AI apps × 10 data sources = 50 custom integrations. Each with its own auth, error handling, and data formatting.

After MCP: N+M Solution

5 AI apps + 10 data sources = 15 integrations. Each app implements one client. Each source implements one server.

MCP HostThe AI application the user interacts with
Claude Desktop, Cursor, VS Code, Antigravity, Windsurf
MCP ClientLightweight connector inside the host, 1:1 with each server
JSON-RPC transport, tool discovery, schema validation
MCP ServerExposes tools, resources, and prompts via the protocol
Your custom server, community servers, npm packages
Data SourceThe real-world system being connected
PostgreSQL, Google Sheets, Slack, GitHub, REST APIs

Before MCP, every AI tool integration was a custom, one-off project. Want your AI assistant to search the web? Build a custom integration. Want it to query your database? Build another one. Want it to read your files? Another one. Each integration was different, fragile, and expensive to maintain.

MCP changes this. Created by Anthropic and now adopted across the industry, the Model Context Protocol is an open standard that provides a single, universal way for AI models to connect to any data source or tool. present or future.

MCP Ecosystem Map

Three layers that make up the MCP architecture

HostsApplications that connect to MCP servers
Claude DesktopCursorAntigravityContinue
ServersServices that expose tools via MCP protocol
Google SheetsPostgreSQLGitHubSlack
TransportsCommunication channels between hosts and servers
stdioHTTP/SSEStreamable HTTP