Model Context Protocol (MCP) Labs
by tsynode
This repository provides a series of labs for learning how to build and use Model Context Protocol (MCP) servers and integrate them with AI Agents. MCP is a standardized protocol that enables AI models to interact with external tools and data sources.
Last updated: N/A
What is Model Context Protocol (MCP) Labs?
The Model Context Protocol (MCP) is a standardized protocol that enables AI models to interact with external tools and data sources, following a client-server architecture.
How to use Model Context Protocol (MCP) Labs?
Each lab directory contains a README with specific instructions. Start with Lab 01 to learn the basics, then proceed to Lab 02 and Lab 03 to explore more advanced scenarios like multiple servers and cloud deployment.
Key features of Model Context Protocol (MCP) Labs
Execute Tools
Access Resources
Get Contextual Information
Standardized Interface
Use cases of Model Context Protocol (MCP) Labs
Interactive testing with Claude Desktop
Retail use case with multiple MCP servers
AWS Cloud Deployment with Fargate
AI-powered functionality across different platforms and models
FAQ from Model Context Protocol (MCP) Labs
What is MCP?
What is MCP?
A standardized protocol for AI models to interact with external tools and data sources.
What is a Host in MCP?
What is a Host in MCP?
The application that needs AI capabilities.
What is a Client in MCP?
What is a Client in MCP?
Part of the host that manages connections to MCP servers.
What is a Server in MCP?
What is a Server in MCP?
Provides tools and resources that the AI can use.
Where can I find the MCP specification?
Where can I find the MCP specification?
At modelcontextprotocol.io