Merge pull request huggingface#17 from vivganes/patch-1

fix typos + add missing links

Author: burtenshaw

units/en/unit0/introduction.mdx

@@ -104,9 +104,9 @@ 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)
 
@@ -128,12 +128,12 @@ Ben is a Machine Learning Engineer at Hugging Face who focuses on building LLM a
 
 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_, it is best 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.