使用说明
MCP-in-Practice-Anthropic-Course
📘 About
This repository documents my learning and implementation of MCP concepts, inspired by Anthropic’s course and expanded with practical examples, patterns, and system-level understanding.
The goal is to move beyond theory and demonstrate how MCP can be used to build structured, scalable, and production-ready AI systems.
🧠 What is MCP?
Model Context Protocol (MCP) is a structured way to connect AI models with external tools, resources, and prompts, enabling more reliable and controllable agentic workflows.
📚 What You'll Learn
- MCP architecture and core concepts
- How MCP clients interact with servers
- Defining and using tools within MCP
- Working with resources and structured context
- Prompt design and integration in MCP systems
- Building and connecting MCP clients
- Debugging and inspecting MCP servers
🚀 Key Topics Covered
🔹 MCP Clients
- Connecting to MCP servers
- Handling requests and responses
🔹 MCP Servers
- Tool definitions
- Server setup and inspection
🔹 Tools
- Creating structured tool interfaces
- Enabling model-to-tool interaction
🔹 Resources
- Defining and accessing external context
- Managing structured data inputs
🔹 Prompts
- Designing reusable prompt templates
- Integrating prompts within MCP workflows
Certification:
