Before MCP, connecting N AI models to M tools required N×M custom integration layers. Each model needed a separate adapter for each tool — Claude needed one adapter for GitHub, another for Jira, another for Slack, and so did every other AI model. With M tools and N models, the ecosystem required N×M integrations to build, maintain, and version.
MCP collapses this to N+M connections. Each tool publishes one MCP server implementing the standard protocol. Each AI client implements one MCP client. The protocol is the contract: any compliant client works with any compliant server without custom glue code.
The analogy is USB replacing the chaos of parallel ports, serial ports, PS/2, and ADB connectors. A shared plug beats N×M adapters. MCP is that plug for AI-tool integration.
The practical payoff: an MCP server you build today works with Claude Desktop, Claude Code, Cursor, and any future MCP-compatible client — without modification. A tool author reaches every model in the ecosystem at once.
The N×M integration problem is the core motivation tested in exam questions about MCP's purpose. Frame your answer in terms of integration count reduction: N×M becomes N+M.