MCP Portal

Introduction to MCP

• What is Model Context Protocol?
• Understanding the MCP architecture
• Core concepts: servers, clients, and resources
• Setting up your first MCP connection
• Basic MCP operations and tools

Duration: 2-3 hours

Prerequisites: Basic understanding of APIs and software development

MCP Client Setup

• Installing Claude Desktop with MCP
• Configuring MCP servers
• Managing MCP connections
• Troubleshooting common issues
• Best practices for client configuration

Duration: 1-2 hours

Prerequisites: None

Building Your First MCP Server

• MCP server architecture and components
• Setting up development environment
• Creating resources and tools
• Implementing MCP protocol handlers
• Testing and debugging MCP servers

Duration: 4-6 hours

Prerequisites: JavaScript/TypeScript or Python knowledge

MCP with Databases

• Connecting to PostgreSQL, MySQL, and MongoDB
• Implementing database operations
• Query optimization and security
• Real-time data synchronization
• Error handling and recovery

Duration: 3-4 hours

Prerequisites: Database fundamentals, SQL knowledge

Web Integration with MCP

• Building web scraping MCP servers
• API integration patterns
• Authentication and authorization
• Rate limiting and caching strategies
• Webhook handling and real-time updates

Duration: 3-5 hours

Prerequisites: HTTP/REST APIs, web development basics

MCP Security & Authentication

• Implementing secure MCP connections
• Authentication strategies and best practices
• Authorization and access control
• Data encryption and privacy protection
• Security auditing and compliance

Duration: 2-3 hours

Prerequisites: Security fundamentals, encryption basics

Enterprise MCP Architecture

• Scaling MCP servers for enterprise use
• Security best practices and compliance
• Load balancing and high availability
• Monitoring and observability
• Performance optimization techniques

Duration: 6-8 hours

Prerequisites: System architecture, DevOps experience

MCP Protocol Deep Dive

• Understanding the MCP specification
• Custom protocol extensions
• Advanced message handling
• Protocol optimization and performance
• Contributing to MCP development

Duration: 5-7 hours

Prerequisites: Advanced programming, protocol design knowledge

AI Integration Patterns

• Integrating MCP with AI models
• Building AI-powered MCP tools
• Context management and memory
• Multi-modal MCP implementations
• Advanced AI workflow patterns

Duration: 4-6 hours

Prerequisites: AI/ML fundamentals, LLM experience

Custom MCP Framework Development

• Building your own MCP framework
• Advanced protocol handling
• Performance optimization techniques
• Framework architecture design
• Open source contribution strategies

Duration: 8-10 hours

Prerequisites: Expert-level programming, framework design experience

📚 Official Documentation

• MCP Specification and Protocol Guide
• Server Development Documentation
• Client Integration Guidelines
• API Reference and Examples

💻 Code Examples

• Sample MCP server implementations
• Client integration examples
• Real-world use case demonstrations
• Best practice code patterns

🎥 Video Tutorials

• Introduction to MCP video series
• Step-by-step implementation guides
• Advanced architecture walkthroughs
• Community showcase sessions

🤝 Community Support

• Discord community for real-time help
• GitHub discussions and issues
• Stack Overflow Q&A
• Regular community office hours

What is MCP?

Model Context Protocol (MCP) is an open standard for connecting AI assistants to external data sources and tools. It enables seamless integration between AI models and various services, databases, APIs, and applications.

MCP provides a standardized way for AI systems to:

• Access external data sources
• Execute tools and functions
• Maintain context across interactions
• Integrate with existing workflows

Key Benefits

• Standardization: Common protocol for AI tool integration
• Security: Controlled access to sensitive resources
• Flexibility: Support for diverse data sources and tools
• Scalability: Enterprise-ready architecture
• Open Source: Community-driven development
• Interoperability: Works across different AI platforms

Getting Started

Ready to start with MCP? Here's your roadmap:

• 1. Install a compatible MCP client (Claude Desktop recommended)
• 2. Browse the MCP servers catalog
• 3. Configure your first MCP server
• 4. Start the "Learn MCP" course
• 5. Join the MCP community
• 6. Build your first custom MCP server

Use Cases

MCP enables powerful AI integrations across various domains:

• Development: Code analysis, debugging, deployment automation
• Data Analysis: Database queries, report generation, visualization
• Content: Document processing, web scraping, content management
• Business: CRM integration, e-commerce automation, analytics
• Research: Data collection, analysis, knowledge management

Architecture Overview

MCP follows a client-server architecture:

• MCP Clients: AI assistants that consume MCP services
• MCP Servers: Services that expose tools and resources
• Protocol: Standardized communication layer
• Transport: Various connection methods (stdio, HTTP, WebSockets)
• Security: Authentication and authorization mechanisms

Community & Support

Join the growing MCP community:

• GitHub: Contribute to MCP development and report issues
• Discord: Chat with other developers and get real-time help
• Documentation: Comprehensive guides and API references
• Examples: Real-world MCP implementations and tutorials
• Forums: Get help and share knowledge with the community
• Office Hours: Regular community Q&A sessions

Contributing

Help grow the MCP ecosystem:

• Submit MCP Servers: Add your server to the registry
• Improve Documentation: Help others learn MCP
• Report Issues: Help identify and fix problems
• Share Use Cases: Inspire others with your implementations
• Contribute Code: Enhance MCP tools and frameworks

Future Roadmap

Exciting developments ahead for MCP:

• Enhanced Security: Advanced authentication and encryption
• Performance: Optimized protocol and caching mechanisms
• Ecosystem: More clients, servers, and integrations
• Standards: Industry adoption and standardization
• Tools: Better development and debugging tools