10 GitHub Repositories to Master AI Agents and MCP

10 GitHub Repositories for Mastering Agents and MCPs

This article provides a curated list of 10 essential GitHub repositories for anyone looking to delve into the world of AI agents and the Model Context Protocol (MCP). It aims to guide users, from beginners to advanced practitioners, in building and understanding agentic AI applications.

Introduction to AI Agents and MCP

AI agents are autonomous software entities designed to perceive their environment, make decisions, and take actions to achieve specific goals. They are crucial for modern AI applications like chatbots and complex multi-agent systems. The Model Context Protocol (MCP) is an open standard that facilitates the connection of AI models with external tools, APIs, and data sources. Both technologies are rapidly advancing and are being adopted by companies to automate tasks and improve efficiency, as AI agents can sometimes outperform human employees in specific roles.

Key GitHub Repositories for Learning:

This selection of repositories offers a comprehensive learning path, covering tutorials, code samples, practical projects, research papers, and even video guides.

1. Learn AI and LLMs from Scratch:

   • Repo: ashishps1/learn-ai-engineering
   • Description: A structured, free resource path for understanding AI and Large Language Models (LLMs) from the basics.

2. Microsoft's AI Agents for Beginners:

   • Repo: microsoft/ai-agents-for-beginners
   • Description: Features 11 lessons with clear explanations and practical examples for building your first AI agents.

3. GenAI Agents Tutorials and Implementations:

   • Repo: NirDiamant/GenAI_Agents
   • Description: Offers in-depth tutorials and projects for Generative AI Agent techniques, built with Jupyter Notebooks for easy understanding.

4. Complete Agentic AI Engineering Course:

   • Repo: ed-donner/agents
   • Description: A 6-week course covering coding and deployment of AI Agents, including code, projects, and lessons.

5. System Prompts and Models of AI Tools:

   • Repo: x1xhlol/system-prompts-and-models-of-ai-tools
   • Description: Collects system prompts, tools, and models from popular AI applications like Devin and Replit Agent to explore architectures and prompt engineering.

6. AI Agents Masterclass (with Video Guides):

   • Repo: coleam00/ai-agents-masterclass
   • Description: Companion repository for a YouTube masterclass series, providing code and resources for step-by-step agent building.

7. Awesome AI Agents (Curated List):

   • Repo: e2b-dev/awesome-ai-agents
   • Description: A comprehensive curated list of the best AI agent frameworks, libraries, and research papers, categorized into open-source and closed-source.

8. Awesome MCP Servers:

   • Repo: punkpeye/awesome-mcp-servers
   • Description: A community-maintained list of Model Context Protocol (MCP) servers, categorized by application area.

9. Awesome MCP Clients:

   • Repo: punkpeye/awesome-mcp-clients
   • Description: A list of top MCP clients, including Python frameworks, desktop chatbots, VSCode extensions, and CLI tools.

10. Awesome LLM Apps with Agents and RAG:

    • Repo: Shubhamsaboo/awesome-llm-apps
    • Description: Showcases applications combining AI agents, RAG, MCP servers, and advanced models, offering inspiration for portfolio projects.

The Future of AI: Agents and MCPs

While LLMs have limitations, the integration of agents and MCP servers offers a promising direction for AI development. These technologies enhance LLMs by providing capabilities for real-time data analysis, internet searching, and automated decision-making, enabling applications like automated stock trading. The article encourages readers to leverage these resources to build their own agentic applications and utilize AI effectively.

About the Author

Abid Ali Awan is a certified data scientist professional focused on machine learning and data science technologies. He 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.

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