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Contents
Introduction
AI agents are autonomous software entities that perceive their environment, make decisions, and take actions to achieve specific goals. They are fundamental to modern artificial intelligence applications, ranging from chatbots to complex multi-agent systems. The Model Context Protocol (MCP) is an open standard designed for connecting AI models with external tools, APIs, and data sources.
Both of these technologies are dominating the AI space, and companies are using them to automate repetitive tasks and reduce workforce, as agentic AI can outperform junior-level employees in certain cases.
In this article, we will review ten GitHub repositories that can help you learn the basics of AI agents and guide you in building agent-based applications. These repositories include tutorials, code samples, hands-on projects, valuable resources, and even YouTube guides to accelerate your learning journey.
10 GitHub Repositories for Mastering Agents and MCPs
1. Learn AI and LLMs from Scratch
Repo: ashishps1/learn-ai-engineering
This repository provides a structured path to understanding AI and large language models (LLMs) from the ground up, using only free resources. Whether you are a beginner or brushing up on the basics, you will find valuable guides and links.
2. Microsoft’s AI Agents for Beginners
Repo: microsoft/ai-agents-for-beginners
Get hands-on with 11 lessons designed to help you build your first AI agents. Clear explanations and practical examples make this an ideal starting point for those wanting to understand agentic systems.
3. GenAI Agents Tutorials and Implementations
Repo: NirDiamant/GenAI_Agents
Are you looking for an in-depth exploration of Generative AI Agent techniques? This repository offers comprehensive tutorials and projects, ranging from basic to advanced concepts, making it perfect for building smart, interactive AI systems. All projects are built using Jupyter Notebook, with detailed descriptions, code, and outputs to help you quickly understand how each application works.
4. Complete Agentic AI Engineering Course
Repo: ed-donner/agents
Learn how to code and deploy AI Agents in 6 weeks with the Agentic AI Engineering course. Follow along with code, projects, and lessons tailored to give you a robust foundation in agent design and deployment.
5. System Prompts and Models of AI Tools
Repo: x1xhlol/system-prompts-and-models-of-ai-tools
Curious about how popular AI tools work under the hood? This repo collects system prompts, tools, and models from the applications like Cursor, Devin, Replit Agent, and more. Explore real-world agent architectures and prompt engineering strategies.
6. AI Agents Masterclass (with Video Guides)
Repo: coleam00/ai-agents-masterclass
This repository is the companion for the masterclass series on YouTube, containing all the code and resources found here. Build and expand on practical agent examples as you learn step-by-step through video tutorials.
7. Awesome AI Agents (Curated List)
Repo: e2b-dev/awesome-ai-agents
This is the ultimate list for anyone interested in autonomous agents. Explore a curated collection of the best AI agent frameworks, libraries, and research papers to accelerate your projects or studies. The list is divided into open-source and closed-source agents.
8. Awesome MCP Servers
Repo: punkpeye/awesome-mcp-servers
Explore the list of Model Context Protocol (MCP) servers. The list is divided into categories such as Art & Culture, Browser Automation, Cloud Platforms, Code Execution, and more. It is maintained by our open-source community, meaning you will find the latest and most popular MCP servers.
9. Awesome MCP Clients
Repo: punkpeye/awesome-mcp-clients
We have checked the list of MCP servers; now, we are checking the list of top MCP clients. These clients can include Python frameworks, desktop chatbots, VSCode extensions, agentic code editors, and CLI tools like Claude Code.
10. Awesome LLM Apps with Agents and RAG
Repo: Shubhamsaboo/awesome-llm-apps
Discover apps that combine AI agents, retrieval-augmented generation (RAG), MCP servers, and cutting-edge models like OpenAI, Anthropic, and Gemini. After learning the basics, you can get inspiration from these projects and start building your portfolio.
Final Thoughts
Large language models have limitations, and we have seen this firsthand. We were excited about the potential of artificial general intelligence, but we are currently witnessing companies manipulate benchmarks to promote their new AI models. So, what is next for AI, and how can we make it better?
One promising direction involves agents and MCP servers. These agents and MCP servers provide additional capabilities for LLMs to extract more information and help automate your workflow.
You can build applications that search the Internet for stock prices, analyze the market and news, and buy or sell shares in real-time. People are making millions by doing this.
So, what are you waiting for? Learn how to build your own agentic application and start using AI the right way.
Abid Ali Awan (@1abidaliawan) is a certified data scientist professional who loves building machine learning models. Currently, he is focusing on content creation and writing technical blogs on machine learning and data science technologies. Abid holds a Master’s degree in technology management and a bachelor’s degree in telecommunication engineering. His vision is to build an AI product using a graph neural network for students struggling with mental illness.