EdgeOne Pages: MCP Client and Server Implementation with Functions
@amylixing
MCP Client and Server Implementation with Functions
Overview
What is EdgeOne Pages: MCP Client and Server Implementation with Functions?
EdgeOne Pages: MCP Client and Server Implementation with Functions is an intelligent chat application built on EdgeOne Pages serverless Functions. It implements a complete Model Context Protocol (MCP) workflow with a Streamable HTTP MCP server and client, enabling browser-based tool interactions like "generating online webpages with a single prompt."
How to use EdgeOne Pages: MCP Client and Server Implementation with Functions?
Deploy via the provided EdgeOne Pages template button or set up locally by cloning the repository, installing dependencies (npm install), configuring a .env file with AI service credentials, and running npm run dev. For remote MCP access, configure your MCP client to point to https://mcp-on-edge.edgeone.site/mcp-server.
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 on EdgeOne Pages
- Complete MCP implementation (Streamable HTTP) per latest specification
- OpenAI‑format compatible backend API
- Deployable with a single click via EdgeOne Pages template
Use cases of EdgeOne Pages: MCP Client and Server Implementation with Functions
- Generating complete webpages from natural language prompts in the browser
- Building intelligent chat applications that leverage MCP tool calling
- Prototyping MCP server‑client workflows on edge infrastructure
- Integrating AI assistants with real‑time context management at the edge
FAQ from EdgeOne Pages: MCP Client and Server Implementation with Functions
What runtime or platform does it require?
It runs on EdgeOne Pages Functions and can be developed locally with Node.js, using EdgeOne’s serverless environment for production.
How is data handled and where does it live?
The README does not specify data location; user‑provided AI service credentials are configured via environment variables in the .env file.
Does it support the latest MCP specification?
Yes, it implements the Streamable HTTP MCP protocol based on the 2025‑03‑26 version of the specification.
Can I use it with any MCP‑compatible client?
Yes, the server is designed to work with any client that supports Streamable HTTP MCP servers, as shown by the JSON configuration example.
What transport protocol does the MCP server use?
The server uses Streamable HTTP transport, as specified in the project’s Streamable HTTP MCP Server section.