MCP is changing how AI applications interact with the systems around them.
An AI agent can now do much more than generate text. It can connect to MCP servers, discover available tools, query internal systems, interact with databases, and trigger actions on behalf of a user.
That capability is powerful, but it creates a new challenge for engineering teams: how do you control what AI agents are allowed to access, how those actions are tracked, and how much they can consume?
As MCP adoption grows, managing each connection independently quickly becomes difficult. Authentication, permissions, tool access, logging, budgets, and security policies can end up scattered across applications and teams.
This is where an enterprise MCP gateway becomes valuable.
