Photo by Author | Chat GPT
Introduction
AI agents are independent software companies that understand, make decisions, and take steps to achieve specific goals. They are fundamental to modern artificial intelligence applications, from chat boats to complex multi -agent system. Model context Protocol (MCP) is an open quality designed to connect AI models with outdoor tools, APIs, and data sources.
Both of these technologies are dominating the AI’s place, and companies are using them repeatedly to automatically automatically and reduce manpower, as the Agent AI can improve junior level employees in some cases.
In this article, we will review the ten gut hubs that can help you learn the basics of AI agents and guide you in building agent -based applications. These reservoirs include lessons, code samples, hand -on projects, valuable resources, and even YouTube guides to accelerate your learning journey.
10 Got Hub Reserves for Mastering Agents and MCPS
1. Learn AI and LLMS from the beginning
Repo: ASHISHSHPS1/LEARN-AI-Engineering
This storage provides a systematic way to understand only free resources, to understand the AI ​​and large language models (LLMS) from the ground. Whether you are early or brushing the basics, you will find valuable leaders and links.
2. AI agent for Microsoft’s early
Repo: Microsoft/AI-AGENTS-BIGHERS
Get hands with 11 lessons designed to help build your first AI agents. It makes it an ideal point for individuals who want to understand the system of agents through clear explanations and practical examples.
3. The lesson and implementation of genai agents
Repo: Nodment/ganai_gents
Are you looking for a depth of a productive AI agent technique? This storage offers comprehensive lessons and projects, which include basic to modern concepts, making it the best of the construction of smart, interactive AI system. All projects are created using the Japter Notebook, which helps you to understand how each application works quickly with detailed explanation, code and output.
4. Full Agent AI Engineering Course
Repo: Ed donor/agent
Learn how to code and deploy AI agents in 6 weeks with the Agent AI Engineering Course. Along with code, projects, and lessons, follow the lessons to give you a strong foundation in the agent design and deployment.
5. System indicating and models of AI tools
Repo: X1xhlol/System-Prompts and Models Off-Ai Tolls
Interestingly interesting how many famous AI’s popular tolls do under the hood? It collects repo system indicators, tools and models, such as cursor, diverse, copy agents, and more from applications. Discover real -world agent architecture and quick engineering strategies.
6. AI agents masterclass (with video guides)
Repo: Colem00/AI-AGENTS-MasterClas
This storage is a masterclass series partner on YouTube, which contains all the codes and resources found here. Build and expand the examples of the practical agent when you learn through video tutorials.
7. Drawing AI agents (Curates List)
Repo: E2B-DEV/Amazing AI-AGENTS
This is the final list for everyone interested in independent agents. To accelerate your plans or studies, discover the best AI agent framework, libraries, and a developed collection of research papers. The list is divided into open source and closed source agents.
8. Amazing MCP servers
Repo: Pankpy/awesome-MCP servers
Discover a list of model context Protocol (MCP) servers. This list is divided into categories such as art and culture, browser automation, cloud platform, code implementation, and much more. It is retained by our open source community, which means you will find the latest and famous MCP server.
9. Amazing MCP Client
Repo: Pankpi/awesome-MCP client
We have checked the list of MCP servers. Now, we are checking the list of top MCP clients. These clients may include CLI tools such as Azigar framework, desktop chat boats, VS code extensions, agent code editors, and cloud codes.
10. Awesome LLM apps with agents and rags
Repo: Shobaamabsu/awesome LLM apps
Discover apps that combine modern models such as AI agents, registration, RAG, MCP servers, and openings, Entropic, and Gemini. After learning the basics, you can get rid of these projects and start building your portfolio.
The final views
There are boundaries of large language models, and we have seen it ourselves. We were passionate about the ability of artificial general intelligence, but we are currently witnessing manipulation in the benchmark to promote our new AI models. So, what is next to AI, and how can we make it better?
A promising direction includes an agent and MCP server. These agents and MCP server provide Additional additional capabilities to extract more information to LLM and automatically make your workflow.
You can create applications that can find the Internet for stock prices, analyze the market and news, and buy or sell shares in real time. People are doing millions by doing this.
So, what are you waiting for? Learn how to prepare your agent’s request and start using AI properly.
Abid Ali Owan For,,,,,,,,,, for,, for,,,, for,,,, for,,, for,,,, for,,,, for,,,, for,,, for,,, for,,, for,,, for,,,, for,,, for,,, for,,,, for,,, for,,,, for,,, for,,, for,,,, for,,, for,,, for,,,, for,,, for,,,, for,,, for,,,, for,,, for,,,, for,,, for,,,, for,,,, for,,,, for,,,, for,,,, for,,,, for,,,, for,,, for,,, for,,, for,,, for,,,,, for,,,, for,,,, for,,,, for,, for,.@1abidaliawan) A certified data scientist is a professional who loves to create a machine learning model. Currently, he is focusing on creating content and writing technical blogs on machine learning and data science technologies. Abid has a master’s degree in technology management and a bachelor’s degree in telecommunications engineering. Its vision is to create AI products using a graph neural network for students with mental illness.