yz174/MCP-server-

EduChain MCP Server

A Model Context Protocol (MCP) server that provides educational content generation tools using the educhain library. This implementation uses mock data generation to demonstrate MCP functionality without requiring API keys.

Project Overview

This assignment demonstrates:

1. Task 1: Setting up the EduChain environment with mock data generation
2. Task 2: Building an MCP server with educational content tools and resources
3. Task 3: Testing the server with Claude Desktop integration

Tools

1. generate_mcqs: Generate multiple-choice questions for topics like Python Programming and Algebra
2. create_lesson_plan: Create comprehensive lesson plans with learning objectives, activities, and assessments

Resources

1. sample-topics: A collection of sample educational topics across programming, mathematics, and science

Installation and Setup

Prerequisites

• Python 3.8+
• Required packages (install via pip):

pip install educhain mcp

Files Structure

educhain-mcp-server/
├── educhain_mcp_server.py          # Main MCP server implementation
├── test_mcp_server.py              # Test script for server functionality
├── claude_desktop_config.json     # Claude Desktop configuration
├── README.md                       # This documentation
└── exploration_scripts/            # Scripts used for investigating educhain
    ├── explore_educhain.py
    ├── examine_model_fields.py
    ├── examine_content_models.py
    └── investigate_api_requirement.py

Usage

1. Test the Server Components

Run the test script to verify functionality:

python test_mcp_server.py

Expected output:

• MCQ generation for Python Programming and Algebra topics
• Lesson plan generation with structured content
• JSON serialization verification

2. Configure Claude Desktop

Copy the claude_desktop_config.json to Claude Desktop's configuration directory:

Windows: %APPDATA%\Claude\claude_desktop_config.json macOS: ~/Library/Application Support/Claude/claude_desktop_config.json Linux: ~/.config/Claude/claude_desktop_config.json

Configuration content:

{
  "mcpServers": {
    "educhain-mcp-server": {
      "command": "python",
      "args": ["C:\\Users\\Ujjwal\\educhain-mcp-server\\educhain_mcp_server.py"],
      "env": {}
    }
  }
}

Note: Update the path in args to match your actual installation directory.

3. Test with Claude Desktop

After configuring Claude Desktop, you can test the following commands:

Generate Multiple Choice Questions

Generate 5 multiple-choice questions on Python loops.

Create Lesson Plans

Provide a lesson plan for teaching algebra.

Access Resources

The server provides sample topics that Claude can reference for educational content generation.

Sample Outputs

MCQ Generation Example

{
  "topic": "Python Programming",
  "num_questions": 3,
  "questions": [
    {
      "question_number": 1,
      "question": "What is Python?",
      "options": ["A high-level programming language", "A type of snake", "A web browser", "A database"],
      "correct_answer": "A high-level programming language",
      "explanation": "Python is a high-level, interpreted programming language known for its simplicity and readability."
    }
  ]
}

Lesson Plan Example

# Lesson Plan: Comprehensive Guide to Python Programming

## Subject: Python Programming
## Grade Level: Beginner

### Learning Objectives
1. Understand the fundamental concepts of Python Programming
2. Apply Python Programming principles to solve problems
3. Demonstrate proficiency in Python Programming techniques
4. Connect Python Programming to real-world applications

### Main Topics
1. Introduction to Python - What is Python and why use it?
2. Basic Syntax - Variables, data types, and operators
3. Control Structures - If statements, loops, and functions
4. Data Structures - Lists, dictionaries, and tuples
5. Error Handling - Try/except blocks and debugging

### Learning Activities
1. Install Python and set up development environment
2. Write your first 'Hello World' program
3. Create a simple calculator using functions
4. Build a to-do list application
5. Debug common Python errors

Technical Implementation

Models Used

• MultipleChoiceQuestion: From educhain.models for structuring MCQs
• MCQList: From educhain.models for question collections
• SimpleLessonPlan: Custom Pydantic model for lesson plan structure

Mock Data Generation

The MockEducationalContentGenerator class provides:

• Template-based MCQ generation for different topics
• Structured lesson plan creation with topic-specific content
• Realistic educational content that demonstrates the MCP capabilities

MCP Server Structure

• Tools: Interactive functions that Claude can call
• Resources: Static content that Claude can access
• Proper Error Handling: Graceful handling of unknown tools/resources
• JSON Schema Validation: Ensures proper input formatting

Testing and Validation

Automated Tests

Run python test_mcp_server.py to verify:

• MCQ generation functionality
• Lesson plan creation
• JSON serialization
• Model validation

Manual Testing with Claude Desktop

1. Verify server connection in Claude Desktop
2. Test MCQ generation with various topics
3. Test lesson plan creation for different subjects
4. Verify resource access functionality

Troubleshooting

Common Issues

Server Connection Failed

• Verify the path in claude_desktop_config.json is correct
• Ensure Python and required packages are installed
• Check that the server script runs without errors

Import Errors

• Run pip install educhain mcp to install dependencies
• Verify Python version is 3.8 or higher

Model Validation Errors

• The implementation uses simplified models to avoid educhain's complex requirements
• All models are tested and validated in the test script

Educational Value

This implementation demonstrates:

• MCP Protocol Usage: Proper implementation of tools and resources
• Educational Content Structure: Using educhain models for realistic educational data
• Mock Data Generation: Creating meaningful educational content without external APIs
• Integration Testing: End-to-end testing from server to Claude Desktop

Future Enhancements

Potential improvements:

1. Expand Topic Coverage: Add more subject areas and question types
2. Dynamic Content: Implement more sophisticated content generation algorithms
3. Assessment Tools: Add quiz generation and grading capabilities
4. Export Functionality: Allow exporting lesson plans and questions to various formats