What can MCP do to enhance AI agents?

The Model Context Protocol (MCP) is gaining traction because it allows AI agents to go beyond static prompts and actually interact with real-world systems. Based on my experience with MCPHubs, here’s how MCP enhances AI agents:

1. Connect to real-time data
   MCP servers allow secure access to files, databases, and APIs. Agents can fetch and process live information instead of relying solely on their training data.

2. Execute operations
   Using tools like Manus and the MCP protocol, AI agents can perform tasks inside external systems—like sending emails, querying databases, or triggering workflows.

3. Boost decision-making
   MCP lets agents use external logic or models to reason more accurately. For example, delegating complex decision logic to a dedicated service can make responses more reliable.

💡 TL;DR: MCP helps AI agents access data, take action, and make smarter decisions—not just talk about them.

Have you tried publishing your own MCP server yet? I shared mine via MCPHubs in under 10 minutes and it was instantly discoverable.