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MCP (Model Context Protocol) lets developers securely connect tools, APIs, and data sources to AI models like Claude, GPT, or Gemini. With MCP, your AI isn't just a chatbot—it becomes a powerful, action-taking agent that can interact with the outside world. MCP is an open protocol by Anthropic that bridges the gap between language models and real-world context. It standardizes how models access: - Resources (read-only data like files or APIs) - Tools (actions like sending emails or fetching weather) - Prompts (reusable instructions to guide agents) Whether you're building local dev tools or production AI apps, MCP ensures your model always has the right context at the right time. In this hands-on course, you'll: - Build your own Weather MCP Server in Node.js/TypeScript - Add Tools, Resources, and Prompts step by step - Connect your server to MCP Client (Claude Desktop and MCP Inspector) - See your AI agent fetch live responses in real time

Maham is an experienced DevRel Content Developer with over 6 years of expertise in open-source frameworks, specializing in creating engaging written and video content for developer communities.
11+ lessons
Interactive
Included
Subscription
What MCP is and why it matters for AI development
Core MCP concepts and architecture
Building and running an MCP server with Node.js & TypeScript
Registering tools, resources, and prompts for AI agents
Basic knowledge of JavaScript/TypeScript
Interest in AI, LLMs, or API development
No prior experience with MCP is required
Developers wanting to build AI agents that take meaningful actions
Teams looking to fetch live data from APIs, files, or databases
Developers wanting to connect LLM models to IDE plugins or command-line tools
Anyone interested in developing composable, multi-server AI workflows
11 lessons
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