What is the architecture of the project?
The system consists of an MCP Streamable HTTP Server, an MCP Client, and a Backend API that coordinates the MCP workflow as the MCP HOST.
@Witusol
基本信息
MCP Client and Server Implementation with Functions
使用下面的配置,将此服务器添加到你的 MCP 客户端。
{
"mcpServers": {
"edgeone-pages-mcp-server": {
"url": "https://mcp-on-edge.edgeone.site/mcp-server"
}
}
}Deploy HTML content to EdgeOne Pages, return the public URL
This project is an intelligent chat application built with EdgeOne Pages Functions technology. It implements a complete Model Context Protocol (MCP) workflow, enabling browser-based access to MCP tool capabilities such as generating online webpages from a single prompt.
Configure a remote MCP service by adding "edgeone-pages-mcp-server" with the URL https://mcp-on-edge.edgeone.site/mcp-server to your MCP client settings. For local development, install dependencies with npm install, set environment variables in .env, and start the dev server with npm run dev. The application can also be deployed directly via the EdgeOne Pages deploy button.
The system consists of an MCP Streamable HTTP Server, an MCP Client, and a Backend API that coordinates the MCP workflow as the MCP HOST.
Set your AI service interface credentials in a `.env` file by copying `.env.example` and filling in the values before starting the development server.
Yes, the backend API at `functions/v1/chat/completions` fully handles OpenAI‑formatted request and response payloads.
The MCP server is based on the Streamable HTTP transport, as defined in the 2025‑03‑26 version of the Model Context Protocol specification.
Click the “Deploy with EdgeOne Pages” badge in the README, or manually configure an EdgeOne Pages project with the provided template.
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