> For the complete documentation index, see [llms.txt](https://davidorban.gitbook.io/sensayhacks/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://davidorban.gitbook.io/sensayhacks/demos/demo-mcp.md).

# 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