MCP Demo

Introduction (15 seconds)

"Welcome to the MCP demo. This protocol enables AI models to dynamically request and receive context during inference, making interactions more efficient and context-aware."

Demonstration (1:15)

1. Initial Setup (30 seconds)

• "Let's create a model that needs to access external data."

• "I'll show how it can request context in real-time."

• "This reduces the need for upfront context provision."

2. Dynamic Context (30 seconds)

• "Let's see how the model requests information on-demand."

• "It will query an external knowledge base."

• "This reduces token usage and improves efficiency."

3. Tool Integration (30 seconds)

• "Let's demonstrate integration with external tools."

• "The model will access a specialized database."

• "This expands its capabilities without direct integration."

4. Standardized Protocol (30 seconds)

• "Let's see how different models can use the same protocol."

• "I'll switch between models while maintaining context."

• "This shows the standardized communication approach."

Conclusion (30 seconds)

"This demo showcases how MCP can:

• Enable dynamic context acquisition

• Reduce token usage

• Expand model capabilities

• Standardize AI communication

The concept has wide-ranging applications in enterprise solutions, research, and customer support."

Key Points to Emphasize

• Dynamic context requests

• Reduced token usage

• Standardized communication

• Expanded capabilities