agent_learning MCP Server
Haozhe-Xing/agent_learning
[](https://agentrank-ai.com/tool/Haozhe-Xing--agent_learning/?utm_source=badge&utm_medium=readme&utm_campaign=agentrank_badge) 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 开发教程 | 每日自动追踪 arXiv 最新论文 | Learn AI Agent Development from Scratch
claude mcp add agentrank -- npx -y agentrank-mcp-server Overview
Haozhe-Xing/agent_learning is a HTML tool licensed under MIT. 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 开发教程 | 每日自动追踪 arXiv 最新论文 | Learn AI Agent Development from Scratch Topics: ai-agent, llm, rag, agent-learning, agentic-workflow, ai-agent-tutorial, dspy, grpo, langchain, large-language-models, mcp, memory-system, multi-agents.
Ranked #1054 out of 24846 indexed tools.
In the top 5% of all indexed tools.
Has 10 contributors.
Ecosystem
Score Breakdown
582 stars → growing community
Last commit 15d ago → recently updated
7/10 issues closed → decent issue management
10 contributors → active community
No dependents → no downstream usage
Weights: Freshness 20% · Issue Health 20% · Dependents 22% · Stars 10% · Contributors 8% · How we score →
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From the README
<div align="center"> # Learn AI Agents from Scratch **A visual, bilingual, and engineering-first textbook for building reliable LLM Agents.** From Function Calling, memory, planning, RAG, and context engineering to Agentic RL, multi-agent systems, evaluation, security, and production deployment. <p> <a href="https://Haozhe-Xing.github.io/agent_learning/en/"></a> <a href="https://Haozhe-Xing.github.io/agent_learning/zh/"></a> </p> <p> <a href="https://github.com/Haozhe-Xing/agent_learning/stargazers"></a> <a href="LICENSE"></a> <a href="https://github.com/Haozhe-Xing/agent_learning/pulls"></a> </p> [中文说明](README_ZH.md) · [Complete directory](#complete-directory) · [Runnable reference agent](#runnable-reference-agent) · [Contributing](#contributing) </div> --- ## What is this repository? `agent_learning` is an open-source AI Agent textbook and learning repository. It is designed for the gap between **"I can call an LLM API"** and **"I can build, evaluate, secure, and deploy anRead full README on GitHub →
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