MCP Mastery: Build AI Apps with Claude, LangChain and Ollama | Udemy [Update 07/2025]
English | Size: 3.5 GB
Genre: eLearning[/center]

Build MCP servers & clients with Python, Streamlit, ChromaDB, LangChain, LangGraph agents, and Ollama integrations

What you'll learn
Build and deploy custom MCP servers with real-world tools, resources, and APIs.
Integrate MCP servers with Claude Desktop, LangChain, and LangGraph workflows.
Implement RAG systems using vector databases for intelligent document retrieval.
Test, secure, and deploy production-ready MCP servers to cloud environments.

Master the Model Context Protocol (MCP) and build production-ready AI applications that connect Claude with real-world data, APIs, and workflows.

As AI adoption accelerates across industries, the Model Context Protocol (MCP) has emerged as the standard for connecting AI models with external systems. Companies are actively seeking developers who can build secure, scalable MCP integrations. This course positions you at the forefront of this rapidly growing field.

What Makes This Course Different

Unlike theoretical courses, you'll build real projects from day one. Each section combines practical coding with essential concepts, ensuring you develop both understanding and hands-on skills. By completion, you'll have a portfolio of working MCP applications ready for production use.

Complete Learning Path: From Basics to Advanced

Foundation & Setup

Master MCP architecture (client, server, transport layers)

Set up a professional development environment with Python, Node.js, and Claude Desktop

Build your first MCP server with live weather API integration

Debug and test MCP connections using Inspector tools

Real-World Integrations

Connect MCP servers directly to Claude Desktop for immediate AI enhancement

Build data analysis servers for Excel, PowerPoint, and SQLite databases

Create file system management tools for automated workflows

Implement web automation using Microsoft Playwright

Advanced AI Workflows

Develop RAG (Retrieval-Augmented Generation) systems with LangChain and vector databases

Build personalized job search applications with MCP tools, resources, and prompts

Create multi-server architectures for complex business processes

Design agentic workflows using local LLMs with Ollama

Production-Ready Applications

Build Streamlit web interfaces for MCP clients

Implement comprehensive testing strategies with MCP Inspector

Deploy servers using multiple transport protocols (STDIO, HTTP)

Create scalable configurations for enterprise environments

Hands-On Projects You'll Build

Real-Time Weather Intelligence Server

Live API integration with error handling

Multi-location weather analysis capabilities

Business Data Analysis Suite

Excel/PowerPoint automation for report generation

SQLite database management with AI-powered queries

Notion integration for professional report publishing

AI-Powered Job Search Assistant

RapidAPI integration for job discovery

Personalized recommendation engine

Complete MCP tools, resources, and prompts implementation

Intelligent Document RAG System

PDF processing and vectorization pipeline

Advanced retrieval mechanisms with LangChain

Multi-document knowledge base management

Streamlit Web Application

Professional UI for MCP interactions

Real-time AI responses and data visualization

Production-ready deployment architecture

Technical Skills You'll Master

MCP Architecture: Deep understanding of protocol specifications and best practices

Python & Node.js: Advanced server development with modern frameworks

AI Integration: Claude Desktop, LangChain, LangGraph, and Ollama

Database Management: SQLite, vector databases, and data processing pipelines

Testing & Debugging: Comprehensive testing strategies and troubleshooting

Who Should Take This Course

AI/ML Developers wanting to integrate AI with real-world systems

Software Engineers looking to add cutting-edge AI skills

Data Scientists interested in building AI-powered data workflows

Entrepreneurs planning AI-enhanced products or services

Technical Professionals seeking to stay current with AI development trends

Prerequisites

Basic Python programming knowledge

Familiarity with APIs and JSON

Understanding of command-line interfaces

No prior MCP or AI development experience required

Course Outcomes

Upon completion, you'll be able to:

Design and implement secure MCP server architectures

Connect AI models to databases, APIs, and external services

Build scalable RAG systems for document intelligence

Create production-ready AI applications with professional UIs

Debug, test, and deploy MCP solutions confidently

Architect multi-agent workflows for complex business processes

All course materials include downloadable code, configuration files, and step-by-step setup guides. Lifetime access with regular updates as MCP evolves.

Who this course is for:
Developers, engineers, and tech enthusiasts who want to master MCP integrations.
Beginners in AI tools looking to build practical, hands-on projects with Claude.
Professionals exploring RAG, LangChain, or LangGraph for AI workflows.
Students and early-career developers aiming to showcase MCP skills in portfolios.

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