mcp-for-beginners and mcp-crash-course

These are complementary resources that serve different learning stages: the comprehensive multi-language curriculum provides foundational MCP concepts, while the hands-on crash course with project-based branches enables practical implementation through specific integration patterns like Streamable-HTTP and LangChain adapters.

mcp-for-beginners
73
Verified
mcp-crash-course
61
Established
Maintenance 22/25
Adoption 10/25
Maturity 16/25
Community 25/25
Maintenance 10/25
Adoption 10/25
Maturity 16/25
Community 25/25
Stars: 15,320
Forks: 4,986
Downloads: —
Commits (30d): 307
Language: Jupyter Notebook
License: MIT
Stars: 142
Forks: 125
Downloads: —
Commits (30d): 0
Language: Python
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 mcp-crash-course

emarco177/mcp-crash-course

Hands-on crash course for the Model Context Protocol (MCP) with project-based branches on Streamable-HTTP, LangChain adapters, and Docker.

This course teaches developers how to build AI applications that connect Large Language Models (LLMs) to external tools and data sources. It takes existing LLMs and shows how to integrate them with other software components to create more intelligent and context-aware AI systems. This is for developers who want to expand the capabilities of their AI agents.

AI-development LLM-integration agentic-AI software-engineering API-integration

Related comparisons

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

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