Is End To End Agentic Ai Automation Lab safe to use?

End To End Agentic Ai Automation Lab has no known CVEs as of the latest MCPpedia security scan. It does not require authentication, so any local process can connect — keep this in mind in shared environments. Licensed under MIT.

How do I install End To End Agentic Ai Automation Lab?

End To End Agentic Ai Automation Lab can be installed by cloning its GitHub repository and following the setup instructions in the README.

What AI clients work with End To End Agentic Ai Automation Lab?

End To End Agentic Ai Automation Lab is compatible with claude-desktop, cursor, claude-code. It uses sse and http transport.

Is End To End Agentic Ai Automation Lab actively maintained?

End To End Agentic Ai Automation Lab is actively maintained — last commit was 5 days ago. It has 70 GitHub stars.

End To End Agentic Ai Automation Lab

Name: End To End Agentic Ai Automation Lab
Author: MDalamin5

by MDalamin5

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.

70 0 tools GitHub

No known CVEs

MIT license

Actively maintained

Last commit 5d ago

Works with most clients

Transport: sse, http

0 tools

Grade F

Edit this pageView history

AI / ML Education

Step 1

Install in your client

Config is the same across clients — only the file and path differ.

Supported in Claude Desktopsse, http · Node 18+

Paste into ~/Library/Application Support/Claude/claude_desktop_config.json

{
  "mcpServers": {
    "end-to-end-agentic-ai-automation-lab": {
      "command": "<see-readme>",
      "args": []
    }
  }
}

Are you the author?

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[![MCPpedia Score](https://mcppedia.org/api/badge/end-to-end-agentic-ai-automation-lab)](https://mcppedia.org/s/end-to-end-agentic-ai-automation-lab)

Read me

What End To End Agentic Ai Automation Lab does

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

Test This Server

This server supports HTTP transport. Be the first to test it — help the community know if it works.

Loading README…

Scored, not listed

Why this score

Five weighted categories — click any category to see the underlying evidence.

Score breakdown

41/100across 5 weighted dimensions

How we score →

0255075100

−59

Security

Maintenance

Efficiency

Documentation

Compatibility

Categoriesclick a row to see evidence

Security

OSV.dev

No known CVEs.

No package registry to scan.

Community

Reviews

Be the first to review

Have you used this server?

Share your experience — it helps other developers decide.

How easy was setup?Did it work reliably?How was the documentation?

Frequently Asked Questions

Is End To End Agentic Ai Automation Lab safe to use?: End To End Agentic Ai Automation Lab has no known CVEs as of the latest MCPpedia security scan. It does not require authentication, so any local process can connect — keep this in mind in shared environments. Licensed under MIT.
How do I install End To End Agentic Ai Automation Lab?: End To End Agentic Ai Automation Lab can be installed by cloning its GitHub repository and following the setup instructions in the README.
What AI clients work with End To End Agentic Ai Automation Lab?: End To End Agentic Ai Automation Lab is compatible with claude-desktop, cursor, claude-code. It uses sse and http transport.
Is End To End Agentic Ai Automation Lab actively maintained?: End To End Agentic Ai Automation Lab is actively maintained — last commit was 5 days ago. It has 70 GitHub stars.

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Edit this pageView history

AI / ML Education

Step 1

Install in your client

Config is the same across clients — only the file and path differ.

Supported in Claude Desktopsse, http · Node 18+

Paste into ~/Library/Application Support/Claude/claude_desktop_config.json

{
  "mcpServers": {
    "end-to-end-agentic-ai-automation-lab": {
      "command": "<see-readme>",
      "args": []
    }
  }
}

Are you the author?

Add this badge to your README to show your security score and help users find safe servers.

Embed in your READMEAbout badges →

[![MCPpedia Score](https://mcppedia.org/api/badge/end-to-end-agentic-ai-automation-lab)](https://mcppedia.org/s/end-to-end-agentic-ai-automation-lab)

Read me

What End To End Agentic Ai Automation Lab does

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

Test This Server

This server supports HTTP transport. Be the first to test it — help the community know if it works.

README

🤖 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 • Key Highlights • Project Architecture • Tech Stack • Getting Started

📖 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.

🚀 Key Highlights

Advanced Agentic Frameworks: Deep dives into LangGraph (StateGraphs, subgraphs, memory, HITL) and AutoGen (RoundRobin, Swarm, custom tools).
Model Context Protocol (MCP): Industry-grade implementations of Anthropic's MCP for tool execution, web search, and Notion integration.
Production RAG Systems: Implementation of Hybrid Search, BM25, LlamaParse, Semantic Routing, and Long/Short-Term Memory (Mem0).
AI Workflow Automation: Zero-code/low-code multi-agent orchestration using n8n and LangFlow.
LLM Fine-Tuning & Serving: Hands-on pipelines for fine-tuning with LoRA/Unsloth and deploying high-throughput inference endpoints with vLLM.
End-to-End Products: Complete full-stack implementations of an AI Interviewer, a Production ATS, and SynapseAI (a stateful, persistent chatbot).

📂 Repository Modules & Projects

The lab is structured progressively. Click to expand each module to see the underlying projects:

1️⃣ Foundations & Data Ingestion (Modules 01 - 02)

01-Pydantic-Data-Validation: Data structuring, field validation, and structured LLM outputs.
02-LangChain-Basics: Embedding models, VectorDBs (FAISS, Pinecone), and basic Retrieval-Augmented Generation (RAG) scratchpads.

2️⃣ LangGraph & Workflow Orchestration (Modules 03 - 04, 13 - 14)

03-LangGraph-Introduction: StateGraphs, Agentic workstations, multi-tool calling.
04-LangGraph-Agentic-Workflows: Agentic RAG, Multi-Agent Supervisors, Human-in-the-Loop (HITL), and Corrective RAG (CRAG).
13-e2e-Deep-Agents: Observation, evaluation, and reliable LangGraph applications.
14-e2e-Ambient-Agent: Building background-running autonomous agents.

3️⃣ AutoGen Multi-Agent Systems (Modules 05 - 09)

05-Autogen-Introduction: Async capabilities, tools, and basic teams.
06-Autogen-HITL-and-Agentic-Orchestrator: Selector Group Chats, Docker code execution, and Graph-based AutoGen.
07-End-To-End-Projects-Autogen: GPT Analyzer (Modular architecture), AI Interviewer.
08-Advanced-Autogen-Team: Swarm logic and Society o

... View full README on GitHub

Loading README…

Scored, not listed

Why this score

Five weighted categories — click any category to see the underlying evidence.

Score breakdown

41/100across 5 weighted dimensions

How we score →

0255075100

−59

Security

Maintenance

Efficiency

Documentation

Compatibility

Categoriesclick a row to see evidence

Security

OSV.dev

No known CVEs.

No package registry to scan.

Community

Reviews

Be the first to review

Have you used this server?

Share your experience — it helps other developers decide.

How easy was setup?Did it work reliably?How was the documentation?

Frequently Asked Questions

Is End To End Agentic Ai Automation Lab safe to use?: End To End Agentic Ai Automation Lab has no known CVEs as of the latest MCPpedia security scan. It does not require authentication, so any local process can connect — keep this in mind in shared environments. Licensed under MIT.
How do I install End To End Agentic Ai Automation Lab?: End To End Agentic Ai Automation Lab can be installed by cloning its GitHub repository and following the setup instructions in the README.
What AI clients work with End To End Agentic Ai Automation Lab?: End To End Agentic Ai Automation Lab is compatible with claude-desktop, cursor, claude-code. It uses sse and http transport.
Is End To End Agentic Ai Automation Lab actively maintained?: End To End Agentic Ai Automation Lab is actively maintained — last commit was 5 days ago. It has 70 GitHub stars.