What you'll learn:
- Model Context Protocol (MCP) Theory
- Model Context Protocol (MCP) Servers (ETA End Of March)
- Model Context Protocol (MCP) Clients (ETA April)
- Model Context Protocol (MCP) Tools, Resources, Prompts
**Course is in beta, new content every few days.**
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 .n
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)
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 MCPServers
