End-to-End-Agentic-Ai-Automation-Lab
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).
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Generative AI Developer | Building agents that remember & reason with LangChain, LangGraph & RAG. | Open to AI/ML Engineer roles.
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MCP Playground is a Streamlit-based interface that allows users to interact with large language models while seamlessly integrating external Multi-Server Command Protocol (MCP) tools. It enables the deployment of multiple FastMCP servers managed via Docker Compose, creating a provider-agnostic client using LangChain and LangGraph.
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.