
The Model Context Protocol (MCP) is an open standard that allows AI assistants to use external tools and access real-time information.
概览
The Model Context Protocol (MCP) is an open standard that allows AI assistants to use external tools and access real-time information. By building an MCP server, you enable AI systems like Claude to extend their capabilities through your custom tools, creating more powerful AI agents. In this workshop, we'll be building and deploying an MCP server with useful tools. You can work through each step by changing branches in this repo. Before starting this workshop, please ensure you have the following installed: - (version 18 or later) - Download - - Install with npm install -g wrangler - - Sign up (free tier is sufficient) - - Download You'll also need a text editor or IDE of your choice (VS Code recommended). - - Download - Only needed for Step 4's optional integration. The workshop can be completed using just the Cloudflare AI Playground. This workshop is designed to be followed step-by-step by implementing the code yourself.
README
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🌐 AI to the World: MCP Workshop
Welcome to the AI to the World MCP Workshop!
The Model Context Protocol (MCP) is an open standard that allows AI assistants to use external tools and access real-time information. By building an MCP server, you enable AI systems like Claude to extend their capabilities through your custom tools, creating more powerful AI agents.
In this workshop, we’ll be building and deploying an MCP server with useful tools. You can work through each step by changing branches in this repo.
Prerequisites
Before starting this workshop, please ensure you have the following installed:
- Node.js (version 18 or later) - Download
- Wrangler CLI - Install with
npm install -g wrangler - A Cloudflare account - Sign up (free tier is sufficient)
- Git - Download
You’ll also need a text editor or IDE of your choice (VS Code recommended).
Optional:
- Claude Desktop - Download - Only needed for Step 4’s optional integration. The workshop can be completed using just the Cloudflare AI Playground.
Getting Started
This workshop is designed to be followed step-by-step by implementing the code yourself. Each step is documented in its own branch of this repository for reference.
-
Follow the steps in sequence, starting with Step 1.
-
Use this repository as reference if you get stuck:
- Browse to the corresponding step branch on GitHub to see the implementation
- Step branches are named
step1,step2, etc. - View the README.md in each branch for detailed instructions
- Check the code in each branch to see the completed implementation
-
If you fall behind during the live workshop, you can use the instructor’s code as a checkpoint.
Each step includes a detailed troubleshooting section to help you overcome common issues.
Workshop Steps
Step 1: Getting Started with MCP Server
Learn the fundamentals of MCP and how AI assistants can use external tools to enhance their capabilities.
Step 2: Adding Custom Tools
Discover how to extend AI capabilities by creating your own custom tools that solve specific problems. We’ll create a randomNumber tool that AI assistants can use for games, simulations, and unpredictable outcomes.
Step 3: Enhanced Random Number with Cloudflare drand
Integrate with external APIs to give AI assistants access to powerful services beyond their training data.
Step 4: Deploying and Using with Cloudflare AI Playground
Make your tools accessible anywhere by deploying to the cloud and connecting to real AI assistants. We’ll use the Cloudflare AI Playground for testing, with an optional section on Claude Desktop integration.
Step 5: Setting Up Cloudflare KV Storage
Learn how to add persistent storage to your MCP server using Cloudflare KV. We’ll set up the infrastructure needed for stateful applications.
安装
This server does not publish a one-line install command.
Open the repository installation guide 新手?先看 mcpskill.org 教程 →