Why it matters for your business
Before MCP, every AI tool needed its own custom integration for every system. MCP lets one connector serve many AI clients, so a company can expose an internal system once and use it from different assistants or agents without rebuilding the integration. Many software vendors now publish MCP servers for their products. The usual integration care still applies: an MCP server grants an AI system real access, so it needs authentication, scoped permissions, logging and a review of which actions it allows before it touches production data.
Example
A professional services firm builds an MCP server for its project management and time tracking systems, exposing read-only tools that look up project status, budgets and hours logged. Staff can ask about their projects from the firm's approved AI assistant, and a separately built reporting agent uses the same MCP server instead of a second custom integration.