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EdgeOne Pages: MCP Client and Server Implementation with Functio…

@icyhd

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icyhd

EdgeOne Pages: MCP Client and Server Implementation with Functions について

MCP Client and Server Implementation with Functions

EdgeOne Pages: MCP Client and Server Implementation with Functions の設定

以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。

{
  "mcpServers": {
    "edgeone-pages-mcp-server": {
      "url": "https://mcp-on-edge.edgeone.site/mcp-server"
    }
  }
}

EdgeOne Pages: MCP Client and Server Implementation with Functions のツール

1

Deploy HTML content to EdgeOne Pages, return the public URL

概要

What is EdgeOne Pages: MCP Client and Server Implementation with Functions?

An intelligent chat application built with EdgeOne Pages Functions technology that implements a complete Model Context Protocol (MCP) workflow, enabling browser-based access to MCP tool capabilities such as generating online webpages with a single prompt.

How to use EdgeOne Pages: MCP Client and Server Implementation with Functions?

Configure remote MCP services in any app that supports Streamable HTTP MCP Server by adding the URL https://mcp-on-edge.edgeone.site/mcp-server to your MCP client configuration. For local development, clone the repository, run npm install, start with npm run dev, and set environment variables in a .env file.

Key features of EdgeOne Pages: MCP Client and Server Implementation with Functions

  • Interactive chat interface built with Next.js and React
  • High-performance edge functions via EdgeOne Pages Functions
  • Complete MCP implementation based on the latest specifications
  • Backend API fully compatible with OpenAI request/response format
  • One-click deployment with EdgeOne Pages template

Use cases of EdgeOne Pages: MCP Client and Server Implementation with Functions

  • Generating online webpages from a single natural‑language prompt
  • Building intelligent chat applications with tool‑augmented LLM interactions
  • Prototyping and deploying MCP‑based workflows at the edge

よくある質問

1

What dependencies are required to run this project locally?

Node.js and a package manager (npm, yarn, pnpm, or bun). An AI service API key must be provided in the `.env` file.

2

How is the MCP transport implemented?

The server uses the Streamable HTTP transport based on the 2025‑03‑26 version of the Model Context Protocol specification.

3

Where does the data live?

All critical business logic runs on EdgeOne Pages Functions (serverless edge compute); no data storage details are provided in the README.

4

What are the authentication requirements for the chat API?

No explicit authentication is described; environment variables for the AI service are configured locally or during deployment.

5

How can I deploy my own instance?

Use the “Deploy with EdgeOne Pages” button in the README or the EdgeOne Pages templates gallery.

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