course-notes-mcp-build-rich-context-ai-apps-with-anthropic
このJupyter Notebookは、Anthropicの技術を用いてリッチなコンテキストを持つAIアプリケーションを構築する方法を学ぶための教材です。具体的な実装例やコードスニペットが含まれており、実践的なスキルを身につけることができます。AIの基礎知識がある方に適しており、実際のアプリケーション開発に役立つ内容が盛り込まれています。
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MCP Course Notes: Build Rich-Context AI Apps with Anthropic 📚
This repository contains the notebooks & code written while taking the DeepLearning.AI short course on the Model Context Protocol (MCP), created in partnership with Anthropic.
🌟 Why MCP?
Modern LLM apps often need to call external tools, search knowledge bases, or inject domain-specific prompts. MCP provides an open, client-server standard that makes those integrations consistent and reusable across projects and teams.
Course Outline
- Lesson 1: Why MCP? - video only
- Lesson 2: MCP Architecture - video only
- Lesson 3: Chatbot Example - video with code example
- Lesson 4: Creating an MCP Server - video with code example
- Lesson 5: Creating an MCP Client - video with code example
- Lesson 6: Connecting the MCP Chatbot to Reference Servers - video with code example
- Lesson 7: Adding Prompt & Resource Features - video with code example
- Lesson 8: Configuring Servers for Claude Desktop - video only
- Lesson 9: Creating and Deploying Remote Server - video with code example
- Lesson 10: MCP Roadmap & Conclusion - video only
This open-source curriculum introduces the fundamentals of Model Context Protocol (MCP) through real-world, cross-language examples in .NET, Java, TypeScript, JavaScript, Rust and Python. Designed for developers, it focuses on practical techniques for building modular, scalable, and secure AI workflows from session setup to service orchestration.
This open-source curriculum introduces the fundamentals of Model Context Protocol (MCP) through real-world, cross-language examples in .NET, Java, TypeScript, JavaScript, and Python. Designed for developers, it focuses on practical techniques for building modular, scalable, and secure AI workflows from session setup to service orchestration.