1. Learn AI and LLMs from Scratch
Repo: coleam00/ai-agents-masterclass
All code and resources from the AI Agents Masterclass video series are included here. Each lesson features code walkthroughs paired with video instruction, making it easy to expand your skillset.
2. Microsoft AI Agents for Beginners
AI agents and MCP integrations are expanding the boundaries of automation and orchestration. These repositories offer the latest tools and knowledge for building, customizing, and deploying agent-based systems. Whether you plan to create bots for data retrieval, market analysis, workflow automation, or research, now is the ideal time to leverage these open-source projects. Dive in, contribute, and build your expertise in the agentic AI landscape.
3. GenAI Agents Tutorials and Implementations
Repo: punkpeye/awesome-mcp-servers
Find categorized directories of Model Context Protocol servers in automation, cloud, art, and code execution. This list is updated by the open-source community.
4. Agentic AI Engineering Course
Repo: Shubhamsaboo/awesome-llm-apps
This showcase features retrieval-augmented generation applications, agentic projects, and MCP integrations using OpenAI, Anthropic, Gemini, and other leading models.
5. System Prompts and Models of AI Tools
Repo: x1xhlol/system-prompts-and-models-of-ai-tools
Gain insight into the prompts and architecture behind AI tools such as Devin, Cursor, and Replit Agent. Learn how leading platforms prompt and manage agents.
6. AI Agents Masterclass (YouTube Companion)
Repositories allow you to combine agent logic, LLM frameworks, and MCP resources for advanced applications.
7. Awesome AI Agents (Curated List)
Repo: NirDiamant/GenAI_Agents
Explore generative agent design, from basic theory to advanced applications. Projects are in Jupyter Notebooks, and every tutorial includes visualized outputs and explanations.
8. Awesome MCP Servers
Repo: ashishps1/learn-ai-engineering
This structured curriculum is designed for beginners and those reviewing AI basics. It includes free guides and resources for mastering artificial intelligence and large language models from the fundamentals up.
9. Awesome MCP Clients
Repo: punkpeye/awesome-mcp-clients
Review a diverse collection of MCP clients including Python frameworks, desktop chatbots, VSCode extensions, and more. This is essential for anyone building or testing MCP integrations.
10. Awesome LLM Apps with Agents and RAG
Repo: ed-donner/agents
A six-week course packed with projects and assignments. This is perfect for engineers aiming to master agent design patterns and deploy them in production environments.
11. LangChain: Applications with LLMs
Repo: microsoft/ai-agents-for-beginners
Start with 11 clear, practical lessons. This repository helps you design, code, and deploy your first AI agents, with projects and real-world examples included.
12. CrewAI: Multi-Agent Collaboration
Repo: hwchase17/langchain
A popular framework for agentic LLM applications, LangChain provides templates, integrations, and sample projects for connecting LLMs with APIs, tools, and external data.
13. Open-Agents: Modular OSS Workflows
Repo: langchain-ai/langgraph
Use LangGraph to structure agent workflows as state machines, helping you create robust and observable pipelines in Python.
14. LangGraph: State Machine for Agents
Repo: open-agents/open-agents
This modular platform enables orchestration of several LLM agents in a workflow. It offers API connectors, memory backends, and support for many modern LLMs.
15. Prompt Engineering Guide (with Agent Examples)
Repo: e2b-dev/awesome-ai-agents
This curated list highlights frameworks, research, and practical libraries for building open and closed-source agents. It is a strong resource for discovery and project planning.
AI Agent and MCP Ecosystem
Repo: joaomdmoura/crewAI
Coordinate multiple agents to solve complex problems. CrewAI includes demos, templates, and use cases such as task routing and collaborative decision making.
Final Thoughts
Repo: datawhalechina/prompt-engineering
This guide covers prompt engineering best practices, complete with agent-focused examples and code snippets. It is suitable for both new and advanced users.
