Anthropic Model Context Protocol (McP) Documentation Project

Official Description

The Model Context Protocol (McP) is an open standard released by Anthropic that enables developers to build secure, two-way connections between their data sources and AI-powered tools. It provides a universal, standardized way to connect AI systems to data sources, eliminating the need for maintaining separate connectors for each data source.

Key aspects of McP:

• Open-source standard for AI-data integration
• Enables direct connection between AI systems and data sources
• Provides standardized interface for tools and resources
• Simplifies development by eliminating need for custom connectors
• Helps AI models produce better, more relevant responses to queries

Live Demo

View the live landing page: https://agent1red.github.io/MyMcPTestProject/

Setting Up GitHub Pages

If you fork this repository and want to set up your own GitHub Pages:

1. Go to your forked repository's Settings
2. In the left sidebar, click on "Pages" under "Code and automation"
3. Under "Source", select "Deploy from a branch"
4. Under "Branch", select "main" and "/root", then click "Save"
5. Wait about 30 seconds for deployment
6. Your site will be available at: https://[your-username].github.io/MyMcPTestProject/
7. You can check deployment status in the "Actions" tab

Technical Architecture

• Developers can expose their data through McP servers
• AI applications can be built as McP clients that connect to these servers
• Servers provide context, tools, and prompts to clients
• Enables AI systems to maintain context across various tools and datasets

Project Creation Process

This entire project was created through a conversation with Claude (Anthropic's AI). Here's the exact conversation flow that generated this repository:

Conversation with Claude

1. Initial Repository Creation:

Human: "create a new repository called MyMcPTestProject"
Claude: [Created the repository using GitHub API]

2. README Creation:

Human: "Add an Readme.md file to that new repository that explains Anthropic Model Context Protocol"
Claude: [Created comprehensive README explaining McP]

3. Landing Page Creation:

Human: "Add an HTML file with css and javascript files that make a one page landing page that describes the Anthropic McP just like we did in the readme and push it to that repo"
Claude: [Created landing page files]

4. GitHub Pages Setup Information:

Human: "how can I view this on github?"
Claude: [Provided GitHub Pages setup instructions]

Human: "does it really take a few minutes?"
Claude: [Clarified GitHub Pages deployment time]

5. Documentation Updates:

Human: "Ok it does work add instructions to the Readme.md for developers that may fork the repo and want to set up a github page. Please make sure this github page link is in there too https://agent1red.github.io/MyMcPTestProject/"
Claude: [Updated README with GitHub Pages instructions and live link]

6. Official Information Integration:

Human: "can you search brave and summarize McP from the website and add it to the Readme.md file and the html page that is in the repo? https://www.anthropic.com/news/model-context-protocol"
Claude: [Used Brave search to find official information and updated both README and landing page with accurate McP details]

Repository Contents

1. Documentation

• README.md: Comprehensive explanation of the Anthropic Model Context Protocol

2. Landing Page

• index.html: Main landing page structure
• styles.css: Styling for the landing page
• script.js: Interactive functionality

Technical Implementation

All files in this repository were generated by AI through natural language conversation. The landing page features:

• Responsive design
• Modern CSS with Flexbox and Grid
• Smooth scrolling navigation
• Interactive elements
• Integration with Font Awesome icons

Key Features

Universal Standard

• Standardized approach to data integration
• Eliminates need for custom connectors
• Secure, two-way connections
• Scalable architecture

Development Benefits

• Simplified integration process
• Consistent interface across data sources
• Better context management
• Improved response relevance

Implementation Framework

• Server-client architecture
• Context and tool management
• Standardized protocols
• Resource optimization

Resources

• Official Announcement
• Anthropic Documentation
• Claude API Documentation
• Implementation Guides

Note on AI Generation

This project serves as an example of AI's capability to:

1. Create technical documentation
2. Generate web development code
3. Manage GitHub repositories
4. Maintain consistency across multiple files
5. Follow complex instructions and create interrelated content

All content was generated through natural language interaction with Claude, demonstrating the potential of AI assistants in software development and documentation tasks.

Screenshot

To add a screenshot of the landing page:

1. Visit the live site: https://agent1red.github.io/MyMcPTestProject/
2. Take a screenshot of the page
3. Create an images directory in your fork
4. Add the screenshot to the images directory
5. Update this section of the README to display your screenshot

License

This documentation project is available for reference and educational purposes.