Running
10
Unit 3 Quiz - Production Ready MCP
🔥
Test your knowledge of MCP in the real world.
\n
\n\n\n\n## 🚀 What to Expect from This Course?\n\nIn this course, you will:\n\n* 📖 **Study Model Context Protocol** in theory, design, and practice.\n* 🧑💻 Learn to **use established MCP SDKs and frameworks**.\n* 💾 **Share your projects** and explore applications created by the community.\n* 🏆 Participate in challenges and **evaluate your MCP implementations**.\n* 🎓 **Earn a certificate of completion** by completing assignments.\n\nOur goal is to help you understand how MCP works and empower you to build your own AI applications.\n\n## 📚 Course Structure\n\nThe course is composed of:\n* **Foundational Units**: Learn MCP concepts in theory.\n* **Use Case Assignments**: Apply learned concepts to real-world problems.\n* **Collaborations**: Featuring the latest MCP implementations and tools from Hugging Face and its partners.\n\n## 🛠️ Prerequisites\n\nTo be able to follow this course, you should have:\n\n* Basic understanding of AI and LLM concepts.\n* Familiarity with software development principles and API concepts.\n* Experience with at least one programming language (Python or TypeScript examples will be shown).\n\nIf you need to brush up on these, the course page suggests these resources:\n* LLM Course: will guide you through the basics of using and building with LLMs.\n* Agents Course: will guide you through building AI agents with LLMs.\n(Please find the links to these specific courses in the main MCP course materials if needed.)\n\n## 🤝 Contribute\n\nThis course is a living project, and **contributions are welcome** 🤗!\n* If you've found a bug or want to improve the course content, please open an issue or a Pull Request in the course's GitHub repository (refer to the course documentation for the specific GitHub link).\n* If you want to add a full section or a new unit, it's best to open an issue first to discuss your ideas with the team.\n\n## ❓ Questions?\n\nPlease open a community discussion on the org page.\n\n\n","html":"\n \n \n
\n\n 
\n
\n \n \n \n
\n 🚀 Unit 3 is here!
\nBuild a production ready MCP application with Anthropic, Slack, and Github integration. Learn to create robust, scalable MCP applications ready for real-world deployment.
\n\n 
\n
\n \n \n \n
\n 🤖 Unit 3.1 for the Hub
\nBuild autonomous agents on the Hugging Face Hub. Create intelligent agents that can operate independently using MCP protocols.
\n\n 
\n
\n \n \n \n \n \n \n
\n 🤖 Using MCP with Local and Open Source Models
\nIn this section, we’ll connect MCP with local and open-source models using Continue, a tool for building AI coding assistants that works with local tools like Ollama.
\n\n 
\n
\n \n \n \n
\n 🎬 Unit 0 Video
\nComplete Introduction to The first parts of the MCP Course. This video is a must-watch for everyone who wants to start the MCP Course.
\n\n 
\n
\n \n \n \n
\n 🔴 Unit 1 Live Stream
\nOn 29th May 8:00 PM CEST we will have a live stream where we will cover Q&A and the MCP Course Unit 1 on MCP fundamentals.
\n\n 
\n
\n \n \n \n
\n 🏆 Get Certified
\nIf you want to get certified, you can do so by completing the MCP Course and passing the certification exam.
\n\n 
\n
\n \n \n
\n 📝 Written Materials
\nTo start learning the MCP Course, you can start with the written materials.
\nWelcome to the 🤗 Model Context Protocol (MCP) Course Organization!
\nThe Model Context Protocol (MCP) Course is your comprehensive guide to understanding, using, and building cutting-edge AI applications that leverage external data and tools through the latest MCP standards. This free course is designed to take you from beginner to an informed practitioner in the world of MCP.
\n📑 Course Resources
\n\n
\n\n\n\n\n \n \n
\n\n 
\n
\n \n \n \n
\n 🚀 Unit 3 is here!
\nBuild a production ready MCP application with Anthropic, Slack, and Github integration. Learn to create robust, scalable MCP applications ready for real-world deployment.
\n\n 
\n
\n \n \n \n
\n 🤖 Unit 3.1 for the Hub
\nBuild autonomous agents on the Hugging Face Hub. Create intelligent agents that can operate independently using MCP protocols.
\n\n 
\n
\n \n \n \n \n \n \n
\n 🤖 Using MCP with Local and Open Source Models
\nIn this section, we’ll connect MCP with local and open-source models using Continue, a tool for building AI coding assistants that works with local tools like Ollama.
\n\n 
\n
\n \n \n \n
\n 🎬 Unit 0 Video
\nComplete Introduction to The first parts of the MCP Course. This video is a must-watch for everyone who wants to start the MCP Course.
\n\n 
\n
\n \n \n \n
\n 🔴 Unit 1 Live Stream
\nOn 29th May 8:00 PM CEST we will have a live stream where we will cover Q&A and the MCP Course Unit 1 on MCP fundamentals.
\n\n 
\n
\n \n \n \n
\n 🏆 Get Certified
\nIf you want to get certified, you can do so by completing the MCP Course and passing the certification exam.
\n\n 
\n
\n \n \n
\n 📝 Written Materials
\nTo start learning the MCP Course, you can start with the written materials.
\n🚀 What to Expect from This Course?
\nIn this course, you will:
\n- \n
- 📖 Study Model Context Protocol in theory, design, and practice. \n
- 🧑💻 Learn to use established MCP SDKs and frameworks. \n
- 💾 Share your projects and explore applications created by the community. \n
- 🏆 Participate in challenges and evaluate your MCP implementations. \n
- 🎓 Earn a certificate of completion by completing assignments. \n
Our goal is to help you understand how MCP works and empower you to build your own AI applications.
\n📚 Course Structure
\nThe course is composed of:
\n- \n
- Foundational Units: Learn MCP concepts in theory. \n
- Use Case Assignments: Apply learned concepts to real-world problems. \n
- Collaborations: Featuring the latest MCP implementations and tools from Hugging Face and its partners. \n
🛠️ Prerequisites
\nTo be able to follow this course, you should have:
\n- \n
- Basic understanding of AI and LLM concepts. \n
- Familiarity with software development principles and API concepts. \n
- Experience with at least one programming language (Python or TypeScript examples will be shown). \n
If you need to brush up on these, the course page suggests these resources:
\n- \n
- LLM Course: will guide you through the basics of using and building with LLMs. \n
- Agents Course: will guide you through building AI agents with LLMs.\n(Please find the links to these specific courses in the main MCP course materials if needed.) \n
🤝 Contribute
\nThis course is a living project, and contributions are welcome 🤗!
\n- \n
- If you've found a bug or want to improve the course content, please open an issue or a Pull Request in the course's GitHub repository (refer to the course documentation for the specific GitHub link). \n
- If you want to add a full section or a new unit, it's best to open an issue first to discuss your ideas with the team. \n
❓ Questions?
\nPlease open a community discussion on the org page.
\n\n","classNames":"hf-sanitized hf-sanitized-5kGNCoyIOvXeiDSPjeLWD"},"users":[{"_id":"62d648291fa3e4e7ae3fa6e8","avatarUrl":"https://cdn-avatars.huggingface.co/v1/production/uploads/62d648291fa3e4e7ae3fa6e8/oatOwf8Xqe5eDbCSuYqCd.png","isPro":true,"fullname":"ben burtenshaw","user":"burtenshaw","type":"user"},{"_id":"61b85ce86eb1f2c5e6233736","avatarUrl":"https://cdn-avatars.huggingface.co/v1/production/uploads/1655385361868-61b85ce86eb1f2c5e6233736.jpeg","isPro":false,"fullname":"Vaibhav Srivastav","user":"reach-vb","type":"user"},{"_id":"68127a479f4404ccda97f42c","avatarUrl":"/avatars/99a30389a75ab943580b61d1a695af95.svg","isPro":false,"fullname":"Rafay Memon","user":"Rafme","type":"user"},{"_id":"6009bde9168be9b5445234bc","avatarUrl":"https://cdn-avatars.huggingface.co/v1/production/uploads/6009bde9168be9b5445234bc/3DFjWEu8JANUGrmGK3AvX.jpeg","isPro":false,"fullname":"Pradipta 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Model Context Protocol, AI Agents, Python, Typescript
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Organization Card
Welcome to the 🤗 Model Context Protocol (MCP) Course Organization!
The Model Context Protocol (MCP) Course is your comprehensive guide to understanding, using, and building cutting-edge AI applications that leverage external data and tools through the latest MCP standards. This free course is designed to take you from beginner to an informed practitioner in the world of MCP.
📑 Course Resources
🚀 Unit 3 is here!
Build a production ready MCP application with Anthropic, Slack, and Github integration. Learn to create robust, scalable MCP applications ready for real-world deployment.
🤖 Unit 3.1 for the Hub
Build autonomous agents on the Hugging Face Hub. Create intelligent agents that can operate independently using MCP protocols.
🤖 Using MCP with Local and Open Source Models
In this section, we’ll connect MCP with local and open-source models using Continue, a tool for building AI coding assistants that works with local tools like Ollama.
🎬 Unit 0 Video
Complete Introduction to The first parts of the MCP Course. This video is a must-watch for everyone who wants to start the MCP Course.
🔴 Unit 1 Live Stream
On 29th May 8:00 PM CEST we will have a live stream where we will cover Q&A and the MCP Course Unit 1 on MCP fundamentals.
🏆 Get Certified
If you want to get certified, you can do so by completing the MCP Course and passing the certification exam.
📝 Written Materials
To start learning the MCP Course, you can start with the written materials.
🚀 What to Expect from This Course?
In this course, you will:
- 📖 Study Model Context Protocol in theory, design, and practice.
- 🧑💻 Learn to use established MCP SDKs and frameworks.
- 💾 Share your projects and explore applications created by the community.
- 🏆 Participate in challenges and evaluate your MCP implementations.
- 🎓 Earn a certificate of completion by completing assignments.
Our goal is to help you understand how MCP works and empower you to build your own AI applications.
📚 Course Structure
The course is composed of:
- Foundational Units: Learn MCP concepts in theory.
- Use Case Assignments: Apply learned concepts to real-world problems.
- Collaborations: Featuring the latest MCP implementations and tools from Hugging Face and its partners.
🛠️ Prerequisites
To be able to follow this course, you should have:
- Basic understanding of AI and LLM concepts.
- Familiarity with software development principles and API concepts.
- Experience with at least one programming language (Python or TypeScript examples will be shown).
If you need to brush up on these, the course page suggests these resources:
- LLM Course: will guide you through the basics of using and building with LLMs.
- Agents Course: will guide you through building AI agents with LLMs. (Please find the links to these specific courses in the main MCP course materials if needed.)
🤝 Contribute
This course is a living project, and contributions are welcome 🤗!
- If you've found a bug or want to improve the course content, please open an issue or a Pull Request in the course's GitHub repository (refer to the course documentation for the specific GitHub link).
- If you want to add a full section or a new unit, it's best to open an issue first to discuss your ideas with the team.
❓ Questions?
Please open a community discussion on the org page.
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