MCP Crash Course: Complete Model Context Protocol in a Day
Build, Connect, Deploy: Master MCP Servers, MCP Clients, Tools & Resources for Powerful LLM Applications
Preview this Course
Please note that this is not a course for beginners. This course assumes that you have a background in software engineering and are proficient in Python. I will be using Cursor IDE but you can use any editor you'd like since we only use basic feature of the IDE like debugging and running scripts .
Ideal students are software developers / data scientists
MCP (Model Context Protocol): A protocol that helps build agents and complex workflows on top of LLMs, providing pre-built integrations, flexibility to switch between LLM providers, and security for your data.
Architecture Components
MCP Hosts: Programs like Claude Desktop, Cursor, Windsurf, or AI tools that want to access data through MCP
MCP Clients: Protocol clients that maintain 1:1 connections with servers (Content ETA April)
MCP Servers: Lightweight programs that each expose specific capabilities through the standardized Model Context Protocol
Local Data Sources: Your computer's files, databases, and services that MCP servers can securely access (Content ETA End of March)
Remote Services: External systems available over the internet (e.g., through APIs) that MCP servers can connect to
(Content ETA End of March)
Authenticaiton
Key Capabilities
Resources: Components that expose data and content from your servers to LLMs
Prompts: Functionality to create reusable prompt templates and workflows
Tools: Features that enable LLMs to perform actions through your server
Sampling: Capability that lets your servers request completions from LLMs
Transports: MCP's communication mechanism between clients and servers
Topic Covered:
MCP + Agent Security best practices
Containerizing MCP Servers
Protocol Flow
MCP + Docker
MCP + LangChain
OAuth 2.0 with MCP featuring Auth0
MCP Deployment (featuring Cloudflare)
A2A - Agent 2 Agent Protocol (WIP)