MCP enables AI agents to become more capable through structured tool access:

• Runtime Discovery: Models can explore available tools and decide which to use based on the task
• Structured Interactions: Tools provide and accept data in well-defined formats, avoiding brittle natural language parsing
• Live Data Access: Instead of being limited to training data, models can pull in current information from business systems
• Function-Call Pattern: Clear request/response format similar to API calls, but with rich context awareness

Real-World Examples

• Retrieving the latest inventory data from a database
• Accessing customer information from CRM systems
• Pulling in Google Drive documents or Slack messages
• Triggering workflows that send emails or create tickets

This capability dramatically enhances what AI assistants can do in enterprise environments.