Master the MCP Protocol Architecture - Understand the host-client-server model, how JSON-RPC 2.0 enables standardized communication, and the difference between STDIO (local) and HTTP (remote) transports.

Distinguish MCP from Similar Patterns - Learn how MCP differs from RAG (retrieval strategy vs. protocol mechanism) and function calling (model API feature vs. protocol interoperability layer).

Implement the Primitives - Build and use Tools (executable actions), Resources (read-only data sources), Prompts (conversation templates) to create intelligent agent systems and more!

Understand Capability Negotiation & Lifecycle - Master the initialization handshake, capability discovery, and how clients and servers negotiate features through tools/list, resources/list, and dynamic updates.

Build MCP Servers with FastMCP3 - Progress from the official Python SDK to FastMCP 3, leveraging decorator-based APIs that reduce development time while maintaining protocol compliance.

Integrate AI Models with MCP - Connect OpenAI GPT models (or other LLMs) to MCP servers, implementing function calling workflows that bridge model intelligence with real-world tools.

Handle Real-World Data Sources - Build practical applications like database query servers and a Youtube Agent, understand pagination, error handling, and how to expose complex data systems through standardized MCP resources.

Implement Security & Approval Patterns - Design human-in-the-loop workflows, handle authentication, manage API keys, and implement approval mechanisms for risky operations.

Debug and Monitor MCP Communication - Use the ping method, inspect JSON-RPC messages, understand Server-Sent Events (SSE) for long-running operations, troubleshoot client-server interactions and more!

Choose the Right Framework - Understand when to use the official MCP Python SDK, versus FastMCP 2/3. When to use LangChain's MCP integration, and when not. When to build your own custom implementation and more!