Is the End-to-End-Agentic-Ai-Automation-Lab MCP server actively maintained?

The End-to-End-Agentic-Ai-Automation-Lab MCP server was last committed 1mo ago and has 1 contributor. Issue health: 100% of issues resolved. AgentRank freshness score reflects real-time maintenance activity.

End-to-End-Agentic-Ai-Automation-Lab MCP Server

Name: MDalamin5/End-to-End-Agentic-Ai-Automation-Lab
Rating: 4.2 (1 reviews)
Author: MDalamin5

MDalamin5/End-to-End-Agentic-Ai-Automation-Lab

Score: 80.6 → 0% Rank #1797 Agent Framework

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This repository contains hands-on projects, code examples, and deployment workflows. Explore multi-agent systems, LangChain, LangGraph, AutoGen, CrewAI, RAG, MCP, automation with n8n, and scalable agent deployment using Docker, AWS, and BentoML.

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Overview

MDalamin5/End-to-End-Agentic-Ai-Automation-Lab is a Jupyter Notebook tool licensed under MIT. This repository contains hands-on projects, code examples, and deployment workflows. Explore multi-agent systems, LangChain, LangGraph, AutoGen, CrewAI, RAG, MCP, automation with n8n, and scalable agent deployment using Docker, AWS, and BentoML. Topics: agentic-ai, agentic-rag, autogen, docker, langchain, langgraph, mcp-server, langsmit, ambient-ai, deep-agents, fine-tuning, guardrails, n8n, reranking, rrf-fusion, vllm.

Ranked #1797 out of 24846 indexed tools.

In the top 8% of all indexed tools.

Ecosystem

Jupyter Notebook MIT

agentic-aiagentic-ragautogendockerlangchainlanggraphmcp-serverlangsmitambient-aideep-agentsfine-tuningguardrailsn8nrerankingrrf-fusionvllm

Score Breakdown

Stars 15% 103

103 stars → growing community

Freshness 25% 1mo ago

Last commit 1mo ago → moderate activity

Issue Health 25% 100%

1/1 issues closed → responsive maintainer

Contributors 10% 1

1 contributor → solo project

Dependents 25% 0

No dependents → no downstream usage

npm Downloads N/A

PyPI Downloads N/A

Forks 41

Description Detailed

License MIT

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

How to Improve

Freshness high impact

Last commit was 49 days ago — a recent commit would boost your freshness score

Contributors medium impact

Single-contributor projects carry bus-factor risk — welcoming contributors boosts confidence

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: 103
Forks: 41
Open Issues: 0
Closed Issues: 1
Contributors: 1
Dependents: —
Language: Jupyter Notebook
License: MIT
Last Commit: 1mo ago

Matched Queries

topic:mcp-server

From the README

<div align="center">

# 🤖 End-to-End Agentic AI & Automation Lab

**A comprehensive, production-grade repository for building, deploying, and managing intelligent AI agents, RAG pipelines, and automated workflows.**

[Overview](#-overview) •
[Key Highlights](#-key-highlights) •
[Project Architecture](#-repository-modules--projects) •
[Tech Stack](#️-tech-stack--tools) •
[Getting Started](#-getting-started)

</div>

---

## 📖 Overview

Welcome to the **End-to-End Agentic AI Automation Lab**. This repository is a massive, hands-on engineering playbook demonstrating how to transition from basic LLM API calls to **complex, multi-agent autonomous systems** and **production-ready AI products**. 

Whether you are looking to build highly reliable Agentic workflows using **LangGraph**, orchestrate multi-agent collaboration via **AutoGen**, implement cutting-edge **Model Context Protocol (MCP)**, or serve fine-tuned local models using **vLLM** and **Unsloth**, this repository has you covered.

Read full README on GitHub →