EdgeOne Pages MCP Server

What does “EdgeOne Pages” MCP Server do?

The EdgeOne Pages MCP Server is a Model Context Protocol (MCP) service designed to deploy HTML content, entire folders, or zip files to EdgeOne Pages, instantly generating a publicly accessible URL. By connecting AI assistants and development tools to EdgeOne’s deployment workflows, this MCP server enables automated publishing of web assets and front-end projects directly from LLM-driven or agentic workflows. Developers can use this service to streamline static site deployment, automate CI/CD for web content, and empower AI tools to manage web hosting and content publishing. The integration with the EdgeOne Pages platform makes it especially suitable for rapid prototyping, documentation hosting, and sharing project outputs in a frictionless, programmatic way.

List of Prompts

No prompt templates are mentioned in the available documentation or repository.

List of Resources

No explicit MCP resource definitions are detailed in the available documentation or repository.

List of Tools

No explicit tool definitions are found in the provided files or documentation. However, the service functionality centers on deploying HTML, folders, or zip files to EdgeOne Pages.

Use Cases of this MCP Server

• Automated Web Content Deployment: Programmatically publish HTML files or folders as websites, streamlining the process for developer agents and AI assistants.
• CI/CD for Static Sites: Integrate with automation pipelines to push documentation, demos, or marketing pages with every code update.
• Instant Shareable Project Previews: Enable AI agents to generate preview URLs for web projects, facilitating rapid iteration and feedback.
• AI-Driven Documentation Hosting: Allow LLMs to maintain, update, and publish technical documentation or reports for teams or the public.
• Education & Prototyping: Support educators and students in instantly publishing project work or prototypes via AI-driven workflows.

How to set it up

Windsurf

1. Prerequisite: Ensure Node.js 18 or higher is installed.
2. Open configuration: Locate the Windsurf configuration file.
3. Add EdgeOne Pages MCP Server:

   {
     "mcpServers": {
       "edgeone-pages-mcp-server": {
         "command": "npx",
         "args": ["edgeone-pages-mcp"],
         "env": {
           "EDGEONE_PAGES_API_TOKEN": ""
         }
       }
     }
   }
   

4. Insert your EdgeOne Pages API token in the EDGEONE_PAGES_API_TOKEN field.
5. Save and restart Windsurf, then verify the configuration.

Claude

1. Prerequisite: Install Node.js 18 or higher.
2. Locate Claude’s config file (usually in the project root).
3. Add the EdgeOne Pages MCP Server block:

   {
     "mcpServers": {
       "edgeone-pages-mcp-server": {
         "command": "npx",
         "args": ["edgeone-pages-mcp"],
         "env": {
           "EDGEONE_PAGES_API_TOKEN": ""
         }
       }
     }
   }
   

4. Insert your API key as above.
5. Save and restart Claude, confirm server registration.

Cursor

1. Ensure Node.js 18+ is installed.
2. Open Cursor’s MCP config file.
3. Configure EdgeOne Pages MCP Server:

   {
     "mcpServers": {
       "edgeone-pages-mcp-server": {
         "command": "npx",
         "args": ["edgeone-pages-mcp"],
         "env": {
           "EDGEONE_PAGES_API_TOKEN": ""
         }
       }
     }
   }
   

4. Add your API token to env.
5. Save and restart Cursor.

Cline

1. Check Node.js 18+ installation.
2. Find the config file for Cline.
3. Add EdgeOne Pages MCP Server as follows:

   {
     "mcpServers": {
       "edgeone-pages-mcp-server": {
         "command": "npx",
         "args": ["edgeone-pages-mcp"],
         "env": {
           "EDGEONE_PAGES_API_TOKEN": ""
         }
       }
     }
   }
   

4. Insert your API token.
5. Save/restart Cline and verify setup.

Securing API Keys

It is recommended to use environment variables for API keys. Example configuration:

{
  "mcpServers": {
    "edgeone-pages-mcp-server": {
      "command": "npx",
      "args": ["edgeone-pages-mcp"],
      "env": {
        "EDGEONE_PAGES_API_TOKEN": "your_api_token_here"
      }
    }
  }
}

How to use this MCP inside flows

Using MCP in FlowHunt

To integrate MCP servers into your FlowHunt workflow, start by adding the MCP component to your flow and connecting it to your AI agent:

Click on the MCP component to open the configuration panel. In the system MCP configuration section, insert your MCP server details using this JSON format:

{
  "edgeone-pages-mcp": {
    "transport": "streamable_http",
    "url": "https://yourmcpserver.example/pathtothemcp/url"
  }
}

Once configured, the AI agent is now able to use this MCP as a tool with access to all its functions and capabilities. Remember to change "edgeone-pages-mcp" to whatever the actual name of your MCP server is and replace the URL with your own MCP server URL.

Overview

Between these tables:
This MCP server is focused and easy to set up for its deployment use case, but lacks depth in tooling, prompts, and resources documentation. For teams needing static site hosting via MCP, it delivers, but is not a comprehensive agentic toolkit. Based on the above, I would rate it a 5/10 for general MCP capabilities.

MCP Score