
MCP Learning Project
A comprehensive learning platform for Model Context Protocol development that teaches MCP concepts through hands-on modules including text processing, file operations, and database integration. Designed as an educational tool with progressive difficulty levels from basic to advanced MCP server development.
README
MCP Learning Project
A comprehensive learning platform for Model Context Protocol (MCP) development. This project is designed to help you learn MCP development from basics to advanced concepts through hands-on experience.
🚀 Quick Start
Prerequisites
- Python 3.8 or higher
- Git
- VS Code or Cursor (recommended)
Installation
-
Clone the repository (if using Git):
git clone <your-repo-url> cd mcp-learning-project
-
Install dependencies:
pip install -r requirements.txt
-
Set up environment:
cp .env.example .env # Edit .env with your configuration
-
Run the basic server:
python src/main.py
📚 Learning Path
Phase 1: Foundation (Start Here!)
- [x] Basic MCP Server - Learn fundamental MCP concepts
- [x] Text Processing Module - Handle text manipulation tasks
- [x] File Operations Module - Work with files and directories
Phase 2: Intermediate
- [ ] Database Integration - Connect with databases
- [ ] API Integration - Work with external APIs
- [ ] Configuration Management - Handle app settings
Phase 3: Advanced
- [ ] Machine Learning - Integrate ML models
- [ ] Web Interface - Create web-based tools
- [ ] Monitoring & Analytics - Track performance
🏗️ Project Structure
mcp-learning-project/
├── src/ # Source code
│ ├── core/ # Core MCP server
│ ├── modules/ # Individual modules
│ ├── shared/ # Shared utilities
│ └── web/ # Web interface
├── tests/ # Test files
├── docs/ # Generated documentation
├── config/ # Configuration files
├── scripts/ # Utility scripts
├── examples/ # Example usage
└── project-docs/ # Project documentation
🛠️ Available Modules
Text Processing Module
- Word Count: Count words in text
- Text Summarization: Create summaries
- Language Detection: Detect text language
- Sentiment Analysis: Analyze text sentiment
File Operations Module
- File Reading: Read file contents
- File Writing: Write data to files
- Directory Operations: List, create, delete directories
- File Format Conversion: Convert between formats
🧪 Testing
Run tests to ensure everything works:
python -m pytest tests/
📖 Documentation
🎯 Your First Steps
- Explore the code: Look at
src/modules/text_processing/
to see how modules work - Run examples: Try the examples in the
examples/
folder - Add your own module: Follow the template in
src/modules/base/
- Test your changes: Use the testing framework
🤝 Contributing
This is a learning project! Feel free to:
- Add new modules
- Improve existing code
- Fix bugs
- Add documentation
- Share your learning experiences
📝 License
This project is for educational purposes. Feel free to use and modify as needed.
🆘 Getting Help
- Check the documentation
- Look at the examples
- Review the test files for usage examples
Happy Learning! 🎉
Start with the basic modules and gradually add more complex features as you learn. Each module is designed to teach you different aspects of MCP development.
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.