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The Model Context Protocol (MCP) is a cutting-edge framework designed to standardize interactions between AI models and client applications. This open-source curriculum offers a structured learning path, complete with practical coding examples and real-world use cases, across popular programming languages including C#, Java, JavaScript, TypeScript, and Python.
Whether you're an AI developer, system architect, or software engineer, this guide is your comprehensive resource for mastering MCP fundamentals and implementation strategies.
- 📘 MCP Documentation – Detailed tutorials and user guides
- 📜 MCP Specification – Protocol architecture and technical references
- 🧑💻 MCP GitHub Repository – Open-source SDKs, tools, and code samples
00-03: Foundations
- 00. Introduction to MCP
Overview of the Model Context Protocol and its significance in AI pipelines. Read more - 01. Core Concepts Explained
In-depth exploration of core MCP concepts. Read more - 02. Security in MCP
Security threats and best practices. Read more - 03. Getting Started with MCP
Environment setup, basic servers/clients, integration. Read more
03.x: Hands-On Labs
04-05: Practical & Advanced
- 04. Practical Implementation
SDKs, debugging, testing, reusable prompt templates. Read more - 05. Advanced Topics in MCP
Multi-modal AI, scaling, enterprise use. Read more - 5.1. MCP Integration with Azure – Guide
- 5.2. Multi modality – Guide
- 5.3. MCP OAuth2 Demo – Guide
- 5.4. Root Contexts – Guide
- 5.5. Routing – Guide
- 5.6. Sampling – Guide
- 5.7. Scaling – Guide
- 5.8. Security – Guide
- 5.9. Web Search MCP – Guide
- 5.10. Realtime Streaming – Guide
- 5.11. Realtime Web Search – Guide
06-10: Community, Best Practices & Labs
- 06. Community Contributions – Guide
- 07. Insights from Early Adoption – Guide
- 08. Best Practices for MCP – Guide
- 09. MCP Case Studies – Guide
- 10. Streamlining AI Workflows: Building an MCP Server with AI Toolkit – Hands On Lab
Explore Code Implementations by Language
Explore Advanced Samples
To get the most out of this curriculum, you should have:
- Basic knowledge of C#, Java, or Python
- Understanding of client-server model and APIs
- (Optional) Familiarity with machine learning concepts
A comprehensive Study Guide is available to help you navigate this repository effectively. The guide includes:
- A visual curriculum map showing all topics covered
- Detailed breakdown of each repository section
- Guidance on how to use sample projects
- Recommended learning paths for different skill levels
- Additional resources to complement your learning journey
Each lesson in this guide includes:
- Clear explanations of MCP concepts
- Live code examples in multiple languages
- Exercises to build real MCP applications
- Extra resources for advanced learners
This content is licensed under the MIT License. For terms and conditions, see the LICENSE.
This project welcomes contributions and suggestions. Most contributions require you to agree to a Contributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us the rights to use your contribution. For details, visit https://cla.opensource.microsoft.com.
When you submit a pull request, a CLA bot will automatically determine whether you need to provide a CLA and decorate the PR appropriately (e.g., status check, comment). Simply follow the instructions provided by the bot. You will only need to do this once across all repos using our CLA.
This project has adopted the Microsoft Open Source Code of Conduct. For more information see the Code of Conduct FAQ or contact [email protected] with any additional questions or comments.
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This project may contain trademarks or logos for projects, products, or services. Authorized use of Microsoft trademarks or logos is subject to and must follow Microsoft's Trademark & Brand Guidelines. Use of Microsoft trademarks or logos in modified versions of this project must not cause confusion or imply Microsoft sponsorship. Any use of third-party trademarks or logos is subject to those third-parties' policies.
