Mcp Workshop
What is Mcp Workshop
mcp-workshop is a repository containing a series of labs designed to teach users how to build and utilize Model Context Protocol (MCP) servers. It provides a structured approach to learning about MCP-compatible tools and resources for AI models.
Use cases
Use cases for mcp-workshop include developing AI models that require interaction with external resources, creating tools that perform specific actions using the MCP protocol, and building applications that need contextual prompts for better AI responses.
How to use
To use mcp-workshop, navigate to the specific lab directory, starting with Lab 01. Each lab includes a README file with detailed instructions on building, running, and testing your MCP server. Follow the commands provided in the README to get started.
Key features
Key features of mcp-workshop include a structured lab environment for learning, a minimal MCP server implementation in Lab 01, and the ability to access tools and resources through the MCP protocol. The labs build upon each other to enhance understanding.
Where to use
mcp-workshop can be used in educational settings, research environments, and by developers looking to create AI applications that leverage the Model Context Protocol for enhanced interaction with external tools and data sources.
Clients Supporting MCP
The following are the main client software that supports the Model Context Protocol. Click the link to visit the official website for more information.
Overview
What is Mcp Workshop
mcp-workshop is a repository containing a series of labs designed to teach users how to build and utilize Model Context Protocol (MCP) servers. It provides a structured approach to learning about MCP-compatible tools and resources for AI models.
Use cases
Use cases for mcp-workshop include developing AI models that require interaction with external resources, creating tools that perform specific actions using the MCP protocol, and building applications that need contextual prompts for better AI responses.
How to use
To use mcp-workshop, navigate to the specific lab directory, starting with Lab 01. Each lab includes a README file with detailed instructions on building, running, and testing your MCP server. Follow the commands provided in the README to get started.
Key features
Key features of mcp-workshop include a structured lab environment for learning, a minimal MCP server implementation in Lab 01, and the ability to access tools and resources through the MCP protocol. The labs build upon each other to enhance understanding.
Where to use
mcp-workshop can be used in educational settings, research environments, and by developers looking to create AI applications that leverage the Model Context Protocol for enhanced interaction with external tools and data sources.
Clients Supporting MCP
The following are the main client software that supports the Model Context Protocol. Click the link to visit the official website for more information.
Content
Model Context Protocol (MCP) Labs
This repository contains a series of labs for learning how to build and use Model Context Protocol (MCP) servers and integrate them with AI Agents.
What is MCP?
The Model Context Protocol (MCP) is a standardized protocol that enables AI models to interact with external tools and data sources. MCP follows a client-server architecture:
- Host: The application that needs AI capabilities
- Client: Part of the host that manages connections to MCP servers
- Server: Provides tools and resources that the AI can use
MCP enables AI models to:
- Execute Tools: Perform actions like searching, calculating, or accessing external systems
- Access Resources: Retrieve data from structured sources via URI templates
- Get Contextual Information: Receive additional context to improve responses
This standardized approach allows AI capabilities to be portable across different platforms and models, creating a consistent interface for AI-powered functionality.
Lab Structure
- Lab 01: Hello Claude - A minimal MCP server with Claude Desktop integration for interactive testing
- Lab 02: Retail MCP Servers - Multiple MCP servers working together for a retail use case
- Lab 03: AWS Cloud Deployment - Deploy MCP servers to AWS Fargate with HTTPS and streaming support
- (More labs will be added in the future)
Getting Started
Each lab directory contains its own README with specific instructions:
- Start with Lab 01 to learn the basics of MCP server implementation and Claude Desktop integration:
cd lab01-hello-claude
- Continue with Lab 02 to explore how multiple MCP servers can work together:
cd lab02-retail-mcp-servers
- Advance to Lab 03 to deploy MCP servers to AWS with Fargate:
cd lab03-aws-cloud-deployment
Be sure to read the README in each lab directory
cat README.md
Resources
Dev Tools Supporting MCP
The following are the main code editors that support the Model Context Protocol. Click the link to visit the official website for more information.
