This repository contains hands-on projects, code examples, and deployment workflows. Explore multi-agent systems, LangChain, LangGraph, AutoGen, CrewAI, RAG, MCP, automation with n8n, and scalable agent deployment using Docker, AWS, and BentoML.

Example implementation of MCP Streamable HTTP client/server in Python and TypeScript.

🏰 An exciting game of programming and Artificial Intelligence

Build the system that prompts your agents. A teaching repo for loop engineering: chapters, an annotated reading list, copy-paste prompts, a runnable example, and a portable agent skill

Labs to explore AI Models, MCP servers, and Agents with the AI Gateway powered by Azure API Management and Microsoft Foundry 🚀

A Swift reimplementation of a Claude Code-style coding agent, built stage by stage to explore what makes coding agents work

This open-source curriculum introduces the fundamentals of Model Context Protocol (MCP) through real-world, cross-language examples in .NET, Java, TypeScript, JavaScript, Rust and Python. Designed for developers, it focuses on practical techniques for building modular, scalable, and secure AI workflows from session setup to service orchestration.

A practical governance framework for organizations adopting the Model Context Protocol (MCP), the open standard that lets AI agents connect to external tools, data sources, and systems.

Cookbook, JSON templates, AI prompts and docs for cutcli — the CapCut / Jianying (剪映) draft CLI. Generate editable video drafts from code, Cursor, Claude Code or any MCP agent.

Context Engineering: Build Consistent, Accurate, Predictable AI Systems

The Developer's Guide to AI - A Field Guide for the Working Developer

From Java Dev to AI Engineer: Spring AI Fast Track