- Promoted by: Anonymous
- Platform: Udemy
- Category: No-Code Development
- Language: English
- Instructor: Anton Voroniuk , Anton Voroniuk Support , Lucas Soares
- Duration: 1 hour(s) 38 minute(s)
- Student(s): 101
- Rate 0 Of 5 From 0 Votes
- Expires on: 2026/01/26
-
Price:
59.990
From MCP Foundations to Real Integrations with Claude and Cursor
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for the "Building AI Integrations with Model Context Protocol (MCP)" course by Anton Voroniuk , Anton Voroniuk Support , Lucas Soares on Udemy.
This course, boasting a 0.0-star rating from 0 reviews
and with 101 enrolled students, provides comprehensive training in No-Code Development.
Spanning approximately
1 hour(s)
38 minute(s)
, this course is delivered in English
and we updated the information on January 22, 2026.
To get your free access, find the coupon code at the end of this article. Happy learning!
The Model Context Protocol (MCP) is emerging as a core standard for how AI systems connect to tools, data, and external capabilities. This course provides a practical, end-to-end understanding of MCP—from first principles to real integrations—so you can design AI agents that scale cleanly across tools, models, and environments.
You’ll start by learning why MCP exists: the M × N integration problem that plagues modern AI systems, and how MCP reframes it into a composable, extensible architecture. From there, you’ll explore MCP’s core components, capabilities, and communication flow—building a clear mental model before touching any implementation.
Once the foundations are solid, the course moves into hands-on development. You’ll build MCP servers and clients from scratch, understand the JSON-RPC 2.0 message protocol that powers MCP, and work with streamable HTTP transport for real-world usage. Finally, you’ll integrate MCP servers with modern AI tooling like Claude Code and Cursor, showing how MCP fits naturally into today’s AI-powered development workflows.
Throughout the course, the focus stays on conceptual clarity, architectural correctness, and real-world applicability—not just getting something working, but understanding why it works and how it scales.
What You’ll Learn
What MCP is, why it exists, and how it solves the AI integration problem
How MCP defines and manages “context” through tools, resources, prompts, and sampling
The roles and responsibilities of MCP hosts, clients, and servers
How MCP communication flows from user request to server execution and back
How to build and test MCP servers and clients using FastMCP
How MCP uses JSON-RPC 2.0 and streamable HTTP transport
How to integrate MCP with modern AI development tools like Claude Code and Cursor
Who This Course Is For
AI engineers and developers building agentic systems
Platform and infrastructure engineers evaluating MCP as a standard
Developers integrating LLMs with tools, data sources, or internal systems
Technical leaders who want a clear architectural understanding of MCP
Why This Course
Most MCP resources focus on snippets and setup. This course focuses on mental models, system design, and real integration patterns, so you can confidently explain MCP, implement it correctly, and use it as a long-term foundation for AI applications.
Enroll now and master the Model Context Protocol!