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The ai-engineering-hub MCP server was last committed 14d ago and has 16 contributors. Issue health: 18% of issues resolved. AgentRank freshness score reflects real-time maintenance activity.

ai-engineering-hub MCP Server

Name: patchy631/ai-engineering-hub
Rating: 3.8 (1 reviews)
Author: patchy631

patchy631/ai-engineering-hub

Score: 69.4 Rank #3912 Search & RAG

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In-depth tutorials on LLMs, RAGs and real-world AI agent applications.

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Overview

patchy631/ai-engineering-hub is a Jupyter Notebook tool licensed under MIT. In-depth tutorials on LLMs, RAGs and real-world AI agent applications. Topics: agents, ai, llms, machine-learning, mcp, rag.

Ranked #3912 out of 24840 indexed tools.

Has 38,010 GitHub stars.

Has 16 contributors.

Ecosystem

Jupyter Notebook MIT

agentsaillmsmachine-learningmcprag

Score Breakdown

Stars 15% 38,010

38,010 stars → extremely popular

Freshness 25% 14d ago

Last commit 14d ago → recently updated

Issue Health 25% 18%

28/153 issues closed → many open issues

Contributors 10% 16

16 contributors → active community

Dependents 25% 0

No dependents → no downstream usage

npm Downloads N/A

PyPI Downloads N/A

Forks 6,248

Description Good

License MIT

Weights: Freshness 20% · Issue Health 20% · Dependents 22% · Stars 10% · Contributors 8% · How we score →

How to Improve

Description low impact

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Issue Health high impact

You have 125 open vs 28 closed issues — triaging stale issues improves health

Dependents medium impact

No downstream dependents detected yet — adoption by other projects is the strongest trust signal

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Markdown

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Details

Stars: 38,010
Forks: 6,248
Open Issues: 125
Closed Issues: 28
Contributors: 16
Dependents: —
Language: Jupyter Notebook
License: MIT
Last Commit: 14d ago

Matched Queries

topic:mcp

From the README

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  <a href="https://trendshift.io/repositories/12800">
    
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# AI Engineering Hub 🚀

Welcome to the **AI Engineering Hub** - your comprehensive resource for learning and building with AI!

## 🌟 Why This Repo?

AI Engineering is advancing rapidly, and staying at the forefront requires both deep understanding and hands-on experience. Here, you will find:
- **93+ Production-Ready Projects** across all skill levels
- In-depth tutorials on **LLMs, RAG, Agents, and more**
- Real-world **AI agent** applications
- Examples to implement, adapt, and scale in your projects

Whether you're a beginner, practitioner, or researcher, this repo provides resources for all skill levels to experiment and succeed in AI engineering.

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## 📋 Table of Contents

- [Getting Started](#-getting-started)
- [Newsletter](#-stay-updated-with-our-newsletter)
- [Projects by Difficulty](#-projects-by-difficulty)
  - [Beginner Projects (22)](#-beginner-

Read full README on GitHub →