agent_learning

by Haozhe-Xing · MCP Server · ★ 269

About agent_learning

🤖 Agent Learning: Learn Agent Development from Scratch The complete open-source roadmap for learning AI Agents — from LLM basics to production-ready Agent systems. Agent Learning () is a systematic, practice-oriented AI Agent learning roadmap and hands-on tutorial covering LLM fundamentals, RAG, memory, tool use, function calling, agentic workflows, LangChain, LangGraph, MCP, multi-agent systems, evaluation, deployment, and agentic RL.

agent-learningagentic-workflowai-agentai-agent-tutorialdspygrpolangchainlarge-language-modelsllmmcp

Quick Facts

Stars269
Forks41
LanguageHTML
CategoryMCP Server
LicenseMIT
Quality Score70.1525053654272/100
Last Updated2026-07-05
Created2026-03-13
Platformsmcp
Est. Tokens~19k

Compatible Skills

These tools work well together with agent_learning for enhanced workflows:

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Frequently Asked Questions

What is agent_learning?

agent_learning is A systematic AI Agent development tutorial covering LLM agents, RAG, tool use, memory systems, multi-agent systems, LangChain, LangGraph, MCP, and agentic RL.|从零开始学 AI Agent 开发 | 系统、全面、实战导向的 Agent 开发教. It is categorized as a MCP Server with 269 GitHub stars.

What programming language is agent_learning written in?

agent_learning is primarily written in HTML. It covers topics such as agent-learning, agentic-workflow, ai-agent.

How do I install or use agent_learning?

You can find installation instructions and usage details in the agent_learning GitHub repository at github.com/Haozhe-Xing/agent_learning. The project has 269 stars and 41 forks, indicating an active community.

What license does agent_learning use?

agent_learning is released under the MIT license, making it free to use and modify according to the license terms.

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