Merge branch 'main' into aswinpajayan-patch-1

Author: burtenshaw

README.md

@@ -19,6 +19,8 @@ You can access the course here 👉 [Coming Soon]
 | 0       | Welcome to the Course                               | Welcome, guidelines, necessary tools, and course overview.                                              |
 | 1       | Introduction to Model Context Protocol              | Definition of MCP, key concepts, and its role in connecting AI models with external data and tools.     |
 | 2       | Building with MCP: Practical Development            | Learn to implement MCP clients and servers using available SDKs and frameworks.                         |
+| 3       | MCP Protocol Deep Dive                            | Explore advanced MCP features, architecture, and real-world integration patterns|
+| 4       | Bonus Units & Collaborations                    | Special topics, partner libraries, and community-driven projects.|
 
 ## Prerequisites
 
@@ -50,4 +52,4 @@ To cite this repository in publications:
   howpublished = {\url{https://github.com/yourusername/mcp-course}},
   note = {GitHub repository},
 }
-``` 
+```

units/en/unit0/introduction.mdx

@@ -43,8 +43,6 @@ The course is composed of:
 
 This **course is a living project, evolving with your feedback and contributions!** Feel free to open issues and PRs in GitHub, and engage in discussions in our Discord server.
 
-After you have gone through the course, you can also send your feedback 👉 using this form [LINK TO FEEDBACK FORM]
-
 ## What's the syllabus?
 
 Here is the **general syllabus for the course**. A more detailed list of topics will be released with each unit.
@@ -54,7 +52,7 @@ Here is the **general syllabus for the course**. A more detailed list of topics
 | 0       | Onboarding                                  | Set you up with the tools and platforms that you will use.                                                             |
 | 1       | MCP Fundamentals, Architecture and Core Concepts | Explain core concepts, architecture, and components of Model Context Protocol. Show a simple use case using MCP.       |
 | 2       | End-to-end Use case: MCP in Action              | Build a simple end-to-end MCP application that you can share with the community. |
-| 3       | Deployed Use case: MCP in Action               | Build a deployed MCP application using a the Hugging Face ecosystem and partners' services.                                        |
+| 3       | Deployed Use case: MCP in Action               | Build a deployed MCP application using the Hugging Face ecosystem and partners' services.                                        |
 | 4       | Bonus Units                                  | Bonus units to help you get more out of the course, working with partners' libraries and services.                                        |
 
 ## What are the prerequisites?
@@ -81,7 +79,7 @@ The above courses are not prerequisites in themselves, so if you understand the
 You only need 2 things:
 
 * _A computer_ with an internet connection.
-* An _Account_: to access the course resources and create projects. If you don't have an account yet, you can create one [here](https://huggingface.co/join) (it's free).
+* An _account_: to access the course resources and create projects. If you don't have an account yet, you can create one [here](https://huggingface.co/join) (it's free).
 
 ## The Certification Process
 
@@ -104,9 +102,9 @@ Since there's a deadline, we provide you a recommended pace:
 
 To get the most out of the course, we have some advice:
 
-1. Join study groups in Discord: studying in groups is always easier. To do that, you need to join our discord server and verify your account.
-2. **Do the quizzes and assignments**: the best way to learn is through hands-on practice and self-assessment.
-3. **Define a schedule to stay in sync**: you can use our recommended pace schedule below or create yours.
+1. [Join study groups in Discord](https://discord.gg/UrrTSsSyjb): Studying in groups is always easier. To do that, you need to join our discord server and verify your account.
+2. **Do the quizzes and assignments**: The best way to learn is through hands-on practice and self-assessment.
+3. **Define a schedule to stay in sync**: You can use our recommended pace schedule below or create yours.
 
 ![Course advice](https://huggingface.co/datasets/mcp-course/images/resolve/main/unit0/3.png)
 
@@ -116,7 +114,7 @@ About the authors:
 
 ### Ben Burtenshaw
 
-Ben is a Machine Learning Engineer at Hugging Face who focuses building LLM applications, with post training and agentic approaches.
+Ben is a Machine Learning Engineer at Hugging Face who focuses on building LLM applications, with post training and agentic approaches.
 
 <!-- ## Acknowledgments -->
 
@@ -128,12 +126,12 @@ Ben is a Machine Learning Engineer at Hugging Face who focuses building LLM appl
 
 Contributions are **welcome** 🤗
 
-* If you _found a bug 🐛 in a notebook_, please open an issue and **describe the problem**.
-* If you _want to improve the course_, you can open a Pull Request.
-* If you _want to add a full section or a new unit_, the best is to open an issue and **describe what content you want to add before starting to write it so that we can guide you**.
+* If you _found a bug 🐛 in a notebook_, please [open an issue](https://github.com/huggingface/mcp-course/issues/new) and **describe the problem**.
+* If you _want to improve the course_, you can [open a Pull Request](https://github.com/huggingface/mcp-course/pulls).
+* If you _want to add a full section or a new unit_, the best is to [open an issue](https://github.com/huggingface/mcp-course/issues/new) and **describe what content you want to add before starting to write it so that we can guide you**.
 
 ## I still have questions
 
 Please ask your question in our discord server #mcp-course-questions.
 
-Now that you have all the information, let's get on board ⛵ 
+Now that you have all the information, let's get on board ⛵ 

units/en/unit1/key-concepts.mdx

@@ -37,7 +37,7 @@ Now that we understand the problem that MCP solves, let's dive into the core ter
 
 MCP is a standard like HTTP or USB-C, and is a protocol for connecting AI applications to external tools and data sources. Therefore, using standard terminology is crucial to making the MCP work effectively. 
 
-When documenting our applications and communincating with the community, we should use the following terminology.
+When documenting our applications and communicating with the community, we should use the following terminology.
 
 </Tip>
 
@@ -68,7 +68,7 @@ Of course, your application's value is the sum of the capabilities it offers. So
 | **Tools** | Executable functions that the AI model can invoke to perform actions or retrieve computed data. Typically relating to the use case of the application. | A tool for a weather application might be a function that returns the weather in a specific location. |
 | **Resources** | Read-only data sources that provide context without significant computation. | A researcher assistant might have a resource for scientific papers. |
 | **Prompts** | Pre-defined templates or workflows that guide interactions between users, AI models, and the available capabilities. | A summarization prompt. |
-| **Sampling** | Server-initiated requests for the Client/Host to perform LLM interactions, enabling recursive actions where the LLM can review generated content and make further decisions. | A writing application reviewing its own output and decide to refine it further. |
+| **Sampling** | Server-initiated requests for the Client/Host to perform LLM interactions, enabling recursive actions where the LLM can review generated content and make further decisions. | A writing application reviewing its own output and decides to refine it further. |
 
 In the following diagram, we can see the collective capabilities applied to a use case for a code agent.
 
@@ -85,4 +85,4 @@ This application might use their MCP entities in the following way:
 
 ### Conclusion
 
-Understanding these key concepts and terminology provides the foundation for working with MCP effectively. In the following sections, we'll build on this foundation to explore the architectural components, communication protocol, and capabilities that make up the Model Context Protocol. 
+Understanding these key concepts and terminology provides the foundation for working with MCP effectively. In the following sections, we'll build on this foundation to explore the architectural components, communication protocol, and capabilities that make up the Model Context Protocol. 

units/en/unit1/mcp-clients.mdx

@@ -248,7 +248,7 @@ Weather API: Get the weather in a specific location
 
 </details>
 
-We can also connect to an MCP server that is hosted on a remote machine. In this case, we need to pass the `SSEServerParameters` to the `ToolCollection.from_mcp` method. 
+We can also connect to an MCP server that is hosted on a remote machine. In this case, we need to pass the `SSEServerParameters` to the `MCPClient` class. 
 
 ```python
 from smolagents.mcp_client import MCPClient

units/en/unit2/gradio-client.mdx

@@ -15,7 +15,7 @@ We'll connect to the MCP server we created in the previous section and use it to
 First, we need to install the `smolagents`, gradio and mcp-client libraries, if we haven't already:
 
 ```bash
-pip install smolagents[mcp] gradio[mcp] mcp
+pip install "smolagents[mcp]" "gradio[mcp]" mcp
 ```
 
 Now, we can import the necessary libraries and create a simple Gradio interface that uses the MCP Client to connect to the MCP Server.
@@ -94,17 +94,12 @@ try:
     model = InferenceClientModel()
     agent = CodeAgent(tools=[*tools], model=model)
 
-    def call_agent(message, history):
-        return str(agent.run(message))
-
-
     demo = gr.ChatInterface(
         fn=lambda message, history: str(agent.run(message)),
         type="messages",
         examples=["Prime factorization of 68"],
         title="Agent with MCP Tools",
         description="This is a simple agent that uses MCP tools to answer questions.",
-        messages=[],
     )
 
     demo.launch()

units/en/unit2/gradio-server.mdx

@@ -167,6 +167,7 @@ textblob
 
 3. Push your code to the Space:
 ```bash
+cp server.py app.py
 git init
 git add app.py requirements.txt
 git commit -m "Initial commit"