deploy-html
Deploy HTML content to EdgeOne Pages, return the public URL
LABSCO SUMMARY
Read it as a reference build, then deploy your own.
The reason to open this is that all three roles — server, client and host — live in one repository as edge functions you can read end to end, which is rare. The hosted endpoint is there to try the flow; the source is there so you can put your own tools behind the same architecture.
What it is
A working example rather than a library: a Next.js chat app whose edge functions implement an MCP Streamable HTTP server, an MCP client, and a chat-completions API that acts as the host coordinating the two. The deployed instance serves an MCP endpoint you can connect to directly.
What you get
- A remote endpoint at https://mcp-on-edge.edgeone.site/mcp-server for any client that supports Streamable HTTP servers
- The server implementation in functions/mcp-server, the client in functions/mcp-client, and the host in functions/v1/chat/completions
- A chat backend that accepts and returns OpenAI-formatted requests, so existing clients can drive it
- A React front end in app/page.tsx you can run locally and reshape
- A one-click deploy path to EdgeOne Pages from the template
- Streamable HTTP as specified in the 2025-03-26 revision of the protocol
Requirements
To use the hosted server, only a client that supports Streamable HTTP — add the URL and you are done. To run your own: npm install and npm run dev, which serves on localhost:3000, plus a .env copied from .env.example and filled in with your AI service configuration. Deploying it is the EdgeOne Pages template flow.
Setup effort
Paste a URL — add the endpoint to your client
USE CASES
01
Seeing an MCP host, client and server work together
Read three small edge functions instead of piecing the roles together from three separate projects.
02
Running MCP on edge functions instead of a server
Deploy the template and get a Streamable HTTP endpoint without provisioning anything that stays running.
03
Driving it from a client you already have
The chat backend speaks the OpenAI request and response format, so existing tooling can talk to it unchanged.
1 tool
Counted once with only startup setup. Other versions, modes or optional credentials may expose a different list.
BEFORE YOU INSTALL
What to know first
Tools you get
1 tool when we connected.
Requires
A client that can reach a remote MCP server over HTTP
CONTEXT COST
Light Standing cost
Rated by the size of the one tool definition that rides along on every turn
INSTALLATION
Connect your client
Add the endpoint to your client.
Server setup
ENDPOINT URL
https://mcp-on-edge.edgeone.site/mcp-server
