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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
| Ch | Title | Description | Link |
|---|---|---|---|
| 00 | Introduction to MCP | Overview of the Model Context Protocol and its significance in AI pipelines, including what is the Model Context Protocol, why standardization matters and practical use cases and benefits | Introduction |
| 01 | Core Concepts Explained | In-depth exploration of the core concepts of MCP, including client-server architecture, key protocol components, and messaging patterns | Core Concepts |
| 02 | Security in MCP | Identifying security threats within MCP-based systems, techniques and best practices for securing implementations | Security |
| 03 | Getting Started with MCP | Environment setup and configuration, creating basic MCP servers and clients, integrating MCP with existing applications | Getting Started |
| 3.1 | First server | Setting up a basic server using the MCP protocol, understanding the server-client interaction, and testing the server | First Server |
| 3.2 | First client | Setting up a basic client using the MCP protocol, understanding the client-server interaction, and testing the client | First Client |
| 3.3 | Client with LLM | Setting up a client using the MCP protocol with a Large Language Model (LLM) | Client with LLM |
| 3.4 | Consuming a server with Visual Studio Code | Setting up Visual Studio Code to consume servers using the MCP protocol | Consuming a server with Visual Studio Code |
| 3.5 | Creating a server using SSE | SSE helps us expose a server to the internet. This section will help you create a server using SSE | Creating a server using SSE |
| 3.6 | Use AI Toolkit | AI toolkit is a great tool that will help you manage your AI and MCP workflow. | Use AI Toolkit |
| 3.7 | Testing your server | Testing is an important part of the development process. This section will help you test use several different tools. | Testing your server |
| 3.8 | Deploy your server | How do you go from local development to production? This section will help you develop and deploy your server. | Deploy your server |
| 04 | Practical Implementation | Using SDKs across different languages, debugging, testing, and validation, crafting reusable prompt templates and workflows | Practical Implementation |
| 05 | Advanced Topics in MCP | Multi-modal AI workflows and extensibility, secure scaling strategies, MCP in enterprise ecosystems | Advanced Topics |
| 06 | Community Contributions | How to contribute code and docs, collaborating via GitHub, community-driven enhancements and feedback | Community Contributions |
| 07 | Insights from Early Adoption | Real-world implementations and what worked, building and deploying MCP-based solutions, trends and future roadmap | Insights |
| 08 | Best Practices for MCP | Performance tuning and optimization, designing fault-tolerant MCP systems, testing and resilience strategies | Best Practices |
| 09 | MCP Case Studies | Deep-dives into MCP solution architectures, deployment blueprints and integration tips, annotated diagrams and project walkthroughs | Case Studies |
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
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 opencode@microsoft.com with any additional questions or comments.
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