mcp-for-beginners and pluralsight-course-mcp-in-practice

One is an open-source curriculum introducing the fundamentals of MCP across multiple languages, while the other is a paid course providing practical application of MCP, making them complementary resources for learning and applying the Model Context Protocol.

mcp-for-beginners
73
Verified
pluralsight-course-mcp-in-practice
43
Emerging
Maintenance 22/25
Adoption 10/25
Maturity 16/25
Community 25/25
Maintenance 10/25
Adoption 3/25
Maturity 15/25
Community 15/25
Stars: 15,320
Forks: 4,986
Downloads: —
Commits (30d): 307
Language: Jupyter Notebook
License: MIT
Stars: 3
Forks: 5
Downloads: —
Commits (30d): 0
Language: C#
License: Apache-2.0
No Package No Dependents
No Package No Dependents

About mcp-for-beginners

microsoft/mcp-for-beginners

This open-source curriculum introduces the fundamentals of Model Context Protocol (MCP) through real-world, cross-language examples in .NET, Java, TypeScript, JavaScript, Rust and Python. Designed for developers, it focuses on practical techniques for building modular, scalable, and secure AI workflows from session setup to service orchestration.

This curriculum teaches developers how to build robust and scalable AI applications by standardizing communication between AI models and various tools or services. It provides hands-on, cross-language examples to help developers integrate AI components seamlessly. The target users are developers who want to create intelligent systems using .NET, Java, TypeScript, JavaScript, Rust, or Python.

AI development application architecture software engineering API integration system design

About pluralsight-course-mcp-in-practice

kamranayub/pluralsight-course-mcp-in-practice

Pluralsight Course: MCP in Practice

Related comparisons

mcp-for-beginners and mcp-crash-course mcp-for-beginners and oorep-mcp mcp-for-beginners and mcptools mcp-for-beginners and artic-mcp mcp-for-beginners and model-context-protocol-resources mcp-for-beginners and MCP-Chinese-Getting-Started-Guide

Scores updated daily from GitHub, PyPI, and npm data. How scores work