MCP — Model Context Protocol — is the standard Anthropic introduced for connecting AI models to external data, tools, and services. It is becoming the de facto plumbing layer for AI applications. Here is the practical definition.
MCP is an open protocol that defines how AI models (like Claude) connect to external data sources, tools, and services. Think of it like USB-C for AI: a standard interface that lets any model talk to any tool.
Before MCP, every AI integration was custom. With MCP, building a connector once means it works with any MCP-compatible AI client.
Reduces integration cost. Vendors build one MCP server; works with Claude, ChatGPT, Cursor, etc.
Enables real agentic AI. Agents that can take action across many tools become practical when those tools speak a common protocol.
Standardizes data access. Your company's Salesforce, Notion, Slack data can all be exposed to AI through MCP servers.
Tool selection. Prefer vendors that have or are building MCP support. It future-proofs your integrations.
Custom builds. If you build custom AI tools internally, build them as MCP servers. They will work with any AI client.
Realistic timeline. MCP ecosystem is maturing rapidly through 2026-2027. Most B2B companies should be aware but not need to deeply understand the protocol details.