Create MCP Clients in JavaScript - Tutorial

In this video, we cover how to create an MCP client that can connect to any MCP server. We will build this from scratch by showing you how to turn a simple chatbot into a chatbot that supports MCP servers. ## Links 🐱 GitHub Repo: https://github.com/alejandro-ao/mcp-clients 🚀 AI Engineer Bootcamp: https://www.aibootcamp.dev/ 😊 Buy me a coffee... or a beer (thanks): https://buymeacoffee.com/alejandro.ao ## What is MCP? MCP (Model Context Protocol) is an open protocol designed to standardize how applications provide context to Large Language Models (LLMs). Think of it as a USB-C port for AI applications, enabling a standardized connection between AI models and various data sources and tools. ## Why Use MCP? - Integration: MCP offers a growing list of pre-built integrations for your LLM. - Flexibility: Easily switch between different LLM providers and vendors. - Security: Follow best practices to secure your data within your infrastructure. ## General Architecture: MCP follows a client-server architecture where a host application can connect to multiple servers. This setup allows for seamless communication between your AI tools and various data sources, both local and remote. ## What You'll Learn: Setting Up Your Environment: - Create and configure your project directory. - Install necessary dependencies and set up TypeScript. - Securely manage your Anthropic API key. Creating the MCP Client: - Set up the basic client structure in TypeScript. - Implement server connection management. - Develop query processing logic to handle tool calls. Interactive Chat Interface: - Build a chat loop for user interaction. - Implement cleanup functionality for graceful exits. Running the Client: - Compile your TypeScript code. - Execute the client with any MCP server. - Troubleshoot common issues and errors. ## How It Works: When you submit a query, the client retrieves available tools from the server, sends the query to Claude (the LLM), executes any requested tool