jupyter-notebook-mcp

The End-to-End Agentic AI Automation Lab is a project portfolio focused on the implementation of agentic AI systems. It offers advanced AI workflow automation using tools like LangChain and RAG pipelines, making it a valuable resource for developers and researchers. Notably, it emphasizes the integration of tools and data based on the Model Context Protocol (MCP).

IntelliNode is an open-source library for orchestrating AI workflows using graph-based architectures. This repository contains educational examples demonstrating the application of multi-agent systems in healthcare and wellness scenarios. Notably, the Nutrition Assessment lab showcases how OpenAI GPT-4 analyzes client notes while Anthropic Claude generates meal plans, highlighting the integration of multiple AI providers in healthcare workflows.

This project demonstrates how to build a fully local AI assistant that provides detailed stock analysis using MCP. It leverages Ollama and LangChain for seamless operation, allowing users to scrape financial data and analyze company details, profit trends, and shareholding patterns.