Online Course Instructor: Multi-Server MCP Integration

Prerequisites

• Claude AI access (Claude 3.5 Sonnet or newer recommended)
• Node.js 18+ installed
• YouTube API access (optional for enhanced features)
• Notion workspace with education template
• Google account with Drive API enabled
• Replicate API token
• Basic understanding of online teaching principles

Environment Preparation

1. API Keys and Authentication
   • YouTube: API key from Google Cloud Console (optional)
   • Notion: Integration token from https://www.notion.so/my-integrations
   • Google Drive: OAuth credentials from Google Cloud Console
   • Replicate: API token from https://replicate.com/account
   • WebResearch: API credentials if required
2. MCP Server Installation

# Install all required MCP servers
npm install -g @youtube-transcript/mcp-server
npm install -g @notion/mcp-server
    npm install -g @replicate/mcp-server
npm install -g @google-drive/mcp-server
npm install -g @sequential-thinking/mcp-server
    npm install -g @webresearch/mcp-server

Claude Configuration

Add the following to your Claude MCP configuration:

{
  "servers": {
    "youtube-transcript": {
      "command": "npx",
      "args": ["@youtube-transcript/mcp-server"],
      "env": {
        "YOUTUBE_API_KEY": "optional_youtube_api_key"
      }
    },
    "notion": {
      "command": "npx",
      "args": ["@notion/mcp-server"],
      "env": {
        "NOTION_API_KEY": "your_notion_api_key",
        "COURSE_DATABASE_ID": "your_course_database_id"
      }
    },
    "replicate": {
      "command": "npx",
      "args": ["@replicate/mcp-server"],
      "env": {
        "REPLICATE_API_TOKEN": "your_replicate_token"
      }
    },
    "google-drive": {
      "command": "npx",
      "args": ["@google-drive/mcp-server"],
      "env": {
        "GOOGLE_CREDENTIALS": "/path/to/credentials.json",
        "GOOGLE_TOKEN": "/path/to/token.json"
      }
    },
    "sequential-thinking": {
      "command": "npx",
      "args": ["@sequential-thinking/mcp-server"],
      "env": {}
    },
    "webresearch": {
      "command": "npx",
      "args": ["@webresearch/mcp-server"],
      "env": {
        "WEBRESEARCH_API_KEY": "your_api_key_if_required"
      }
    }
  }
}

Step 1: Initial Setup and Testing

1. Verify All Servers Are Connected

"Please verify that all MCP servers are connected: YouTube Transcript, Notion, Replicate Flux, Google Drive, Sequential Thinking, and WebResearch."

2. Test Each Server Individually
   • YouTube: “Extract transcript from a Khan Academy calculus video”
   • Notion: “Show my course management dashboard”
   • Replicate: “Generate a simple diagram of a neural network”
   • Google Drive: “List my course folders”
   • Sequential Thinking: “Break down the concept of recursion”
   • WebResearch: “Find recent developments in machine learning education”

Step 2: Teaching Method Analysis

Analyze Successful Educators:

"Extract and analyze teaching methods from top-rated machine learning courses on YouTube:
1. Find videos from Andrew Ng, 3Blue1Brown, and StatQuest
2. Extract their explanation techniques for neural networks
3. Identify their visual teaching strategies
4. Note their pacing and repetition patterns
5. Analyze how they handle complex mathematics"

Compare Teaching Styles:

"Compare different approaches to teaching gradient descent:
- Extract explanations from 5 different educators
- Identify common analogies used
- Note visualization techniques
- Analyze mathematical vs intuitive approaches
- Create a best practices summary"

Student Engagement Analysis:

"Analyze high-engagement moments in educational videos:
1. Identify timestamps with most replays
2. Extract explanations at those points
3. Analyze what makes those sections effective
4. Note visual aids used
5. Create engagement strategy guide"

Step 3: Course Management in Notion

Set Up Student Tracking:

"Create student progress tracking system in Notion:
- Student roster with profiles
- Assignment completion tracker
- Participation grades
- Quiz and exam scores
- Individual progress notes
- Office hours attendance"

Module Organization:

"Organize my Machine Learning course in Notion:
Module 1: Introduction to ML
- Learning objectives
- Lecture notes
- Assignments
- Resources
- Student FAQ

[Repeat for all 12 modules]"

Assignment Management:

"Create assignment tracking system:
1. Assignment database with due dates
2. Submission status tracker
3. Grading rubrics
4. Feedback templates
5. Late submission policies
6. Grade calculation formulas"

Step 4: Visual Content Creation

Generate Concept Diagrams:

"Using Replicate Flux, create visual aids for my neural networks module:
1. Simple perceptron diagram
2. Multi-layer network architecture
3. Backpropagation flow chart
4. Activation function comparisons
5. Training process animation frames"

Create Infographics:

"Design infographics for key concepts:
- Machine Learning algorithm decision tree
- Supervised vs Unsupervised learning comparison
- Model evaluation metrics cheat sheet
- Feature engineering process
- Common pitfalls and solutions"

Visual Metaphors:

"Generate visual metaphors to explain:
1. Gradient descent as hiking down a mountain
2. Overfitting as memorizing vs understanding
3. Neural networks as team decision-making
4. Regularization as simplification
5. Cross-validation as practice tests"

Step 5: Content Organization in Drive

Create Course Structure:

"Organize my Machine Learning course in Google Drive:
/ML_Course_2024/
  /Module_01_Introduction/
    /Lectures/
    /Assignments/
    /Solutions/
    /Resources/
  /Module_02_Supervised_Learning/
  [...continue for all modules]
  /Exams/
  /Student_Submissions/
  /Supplementary_Materials/"

Resource Libraries:

"Build categorized resource library:
- Research papers (by topic)
- Code examples (by algorithm)
- Dataset repository
- Video tutorials
- Interactive notebooks
- Industry case studies"

Version Control:

"Set up content versioning system:
1. Current semester materials
2. Archive of previous versions
3. Update tracking document
4. Student-accessible folders
5. Instructor-only resources"

Step 6: Complex Topic Breakdown

Using Sequential Thinking:

"Break down 'Backpropagation Algorithm' for beginners:
1. Start with simple error correction concept
2. Introduce chain rule from calculus
3. Show single neuron weight update
4. Expand to network of neurons
5. Demonstrate with numerical example
6. Connect to code implementation"

Multiple Explanation Paths:

"Create three different explanations for convolution:
1. Mathematical approach with formulas
2. Visual approach with sliding windows
3. Intuitive approach with image filtering analogy
Each with increasing complexity levels"

Problem-Solving Demonstrations:

"Design step-by-step solution for a classification problem:
1. Problem understanding and data exploration
2. Feature selection reasoning
3. Model choice justification
4. Training process walkthrough
5. Evaluation and interpretation
6. Improvement strategies"

Step 7: Continuous Content Updates

Research Latest Developments:

"Use WebResearch to find updates for my course:
- New ML frameworks and tools
- Recent breakthrough papers
- Industry adoption case studies
- Emerging best practices
- Updated benchmark results"

Incorporate Current Examples:

"Find and integrate current real-world examples:
1. Latest AI applications in healthcare
2. Recent ML failures and lessons learned
3. New regulatory considerations
4. Current job market trends
5. Emerging ethical concerns"

Advanced Teaching Workflows

Adaptive Learning Paths:

"Create differentiated instruction materials:
1. Identify struggling students from Notion tracking
2. Research alternative explanations on YouTube
3. Generate simplified visual aids
4. Create remedial exercises
5. Organize in separate Drive folder
6. Track improvement in Notion"

Interactive Session Preparation:

"Prepare for live Q&A session:
1. Analyze common questions from previous cohorts
2. Research latest answers to technical questions
3. Create visual aids for likely topics
4. Prepare code demonstrations
5. Organize quick-reference materials"

Peer Learning Facilitation:

"Set up peer learning system:
1. Create group project guidelines in Notion
2. Generate collaboration diagrams
3. Research successful peer learning methods
4. Organize shared Drive folders
5. Design peer evaluation rubrics"

Student Support Workflows

Office Hours Optimization:

"Prepare for efficient office hours:
1. Review student progress in Notion
2. Identify common struggle points
3. Prepare targeted explanations
4. Create visual aids for frequent questions
5. Organize resources for quick sharing"

Personalized Feedback:

"Generate comprehensive assignment feedback:
1. Review submission in Drive
2. Check against rubric in Notion
3. Research specific improvement resources
4. Create visual explanation of errors
5. Write constructive feedback
6. Track in student progress notes"

Assessment and Evaluation

Exam Preparation:

"Design comprehensive exam materials:
1. Research question types from top courses
2. Create visual problems using Replicate
3. Develop rubrics in Notion
4. Organize in secure Drive folder
5. Prepare solution guides with explanations"

Performance Analysis:

"Analyze class performance:
1. Extract grade data from Notion
2. Identify problem areas
3. Research remediation strategies
4. Create improvement plans
5. Generate visual progress reports"

Best Practices

1. Daily Teaching Routine:
   • Check student questions in Notion
   • Update course announcements
   • Prepare daily materials
   • Review and respond to submissions
2. Weekly Course Maintenance:
   • Analyze student progress patterns
   • Update content based on feedback
   • Create new visual aids as needed
   • Research supplementary materials
3. Module Preparation:
   • Research latest teaching methods
   • Update examples and case studies
   • Generate new visual content
   • Organize materials systematically
4. Student Engagement:
   • Monitor participation metrics
   • Adapt teaching to student needs
   • Provide timely feedback
   • Celebrate student achievements

Troubleshooting Common Issues

Technical Difficulties:

• Test all platforms before class
• Have backup materials ready
• Provide clear technical guides
• Offer alternative access methods

Student Confusion:

• Identify confusion points early
• Create multiple explanations
• Use visual aids extensively
• Provide additional resources

Content Relevance:

• Regularly update examples
• Connect to current events
• Show practical applications
• Invite industry speakers

Example Teaching Scenarios

Difficult Concept Introduction:

"Introduce transformer architecture:
1. Research best explanations on YouTube
2. Create building-block visuals
3. Break down with Sequential Thinking
4. Prepare interactive examples
5. Organize supporting materials"

Lab Session Management:

"Coordinate coding lab session:
1. Prepare starter code in Drive
2. Create visual debugging guides
3. Set up progress tracking in Notion
4. Research common error solutions
5. Prepare walkthrough materials"

Guest Lecture Coordination:

"Prepare for industry guest speaker:
1. Research speaker's background
2. Create introduction materials
3. Prepare student questions
4. Organize recording setup
5. Plan follow-up activities"