Description
Mastering MCP: Beginner to Pro Across the AI Ecosystem. This course teaches participants how to use the Model Context Protocol (MCP) across major AI platforms and frameworks to build intelligent, context-aware, and memory-aware systems. This course introduces learners to the evolving world of MCP and teaches them how to leverage its full capabilities in industry-leading tools. Designed for all levels, from no-code enthusiasts to Python developers, this course provides a hands-on journey from basic concepts to advanced integrations. Participants will explore how to implement and extend MCP across high-end AI platforms and gain hands-on experience with tools used by industry leaders. By the end of the course, participants will not only understand the core mechanics of MCP, but will also be able to implement it across a variety of frameworks to build scalable, intelligent, and context-aware AI systems.
What you will learn
- Basics of Model Context Protocol (MCP):
- What is MCP?
- What are Model, Context and Protocol?
- History and transition to MCP.
- Key features and benefits of MCP.
- Its role in building Contextual and Memory-Aware AI systems.
- From No-Code to Pro-Code:
- Starting with visual user interfaces and transitioning to Python-based development.
- LangChain:
- Build complex Agent workflows and memory chains with MCP integration.
- Langchain-Gemini-Sqlite MCP Server.
- LlamaIndex:
- Implement Retrieval-Augmented Generation (RAG) pipelines for smarter context management.
- LlamaIndex-Azure OpenAI-Filesystem MCP.
- OpenAI Agents SDK:
- Using MCP in GPT-based applications with advanced Prompt Engineering and Session Management.
- OpenAI SDK and Azure MCP Server.
- Google ADK:
- Integrate Google tools with MCP-based workflows.
- Google ADK and Paypal MCP Server.
- Claude (Anthropic):
- Working with high-context, security-centric AI models.
- A quick introduction to Anthropic and Claude and why Anthropic is mentioned for MCP.
- Demo using Claude Desktop.
- Enable MCP Server Filesystem in Claude.
- Enable Sqlite MCP Server in Claude.
- Azure OpenAI:
- Deploy MCP-equipped models in Enterprise-Ready environments.
- Gemini (Google DeepMind):
- Exploring the leading edge of multimodal MCP applications.
- MCP main architecture:
- The main architecture of the MCP.
- Key components – deepening.
- What is JSON-RPC 2.0?
- MCP transport layer.
- Transport mechanism – STDIO vs. SSE.
- Other items:
- How to trend on Github Stars.
- Working on prerequisites for future lab exercises.
- Build your own MCP Server.
This course is suitable for people who:
- No-Code creators looking to level up with Python.
- Developers and engineers interested in cross-platform AI design.
- Product teams that are building memory-aware assistants or RAG systems.
- AI enthusiasts exploring advanced prompting, agents, and context management.
- Beginners in Model Context Protocol (MCP).
- Those who want to understand No-Code and Python Code for any use case.
- No-Code enthusiasts and Citizen Developers.
- Machine learning engineers and AI specialists.
- Product Managers and Tech Leads.
Course details
- Publisher: Udemy
- Instructor: Kshitij Joy (Cloud Alchemy)
- Training level: Beginner to advanced
- Training duration: 4 hours and 16 minutes
- Number of lessons: 72
Course syllabus as of 2025/9
Prerequisites for the Mastering MCP: Beginner to Pro Across the AI Ecosystem course
- Basic Understanding of Generative AI
- Basic Understanding of Python
- Basic Understanding of Large Language Model (LLM)
- How to use LLMs with Python
- Understanding of Azure / Open AI / Google Gemini
- Basic Understanding of AI Agents
Course images
Sample course video
Installation Guide
After Extract, view with your favorite player.
Subtitles: None
Quality: 720p
Download link
Downloadly
Rapidgator link
File(s) password: www.downloadly.ir
File size
1.4 GB
