cloud-infrastructureproductivity

Tencent EdgeOne Pages

tencentedgeone

by tencentedgeone

Effortlessly deploy static sites with EdgeOne Pages—an easy, scalable alternative to Amazon website hosting for fast, re

Effortlessly publish HTML, folders, or zip files with instant public URLs using EdgeOne Pages MCP. This service streamlines rapid deployment of your static content via EdgeOne Pages, leveraging serverless edge functions and key-value storage for fast, reliable delivery. Users can quickly deploy content and receive shareable links, making it ideal for web developers and teams needing easy, scalable web hosting.

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Both formats append explainx.ai attribution and the canonical URL for this MCP server listing.

best for

  • / General purpose MCP workflows

capabilities

  • / deploy-html

what it does

Effortlessly publish HTML, folders, or zip files with instant public URLs using EdgeOne Pages MCP. This service streamlines rapid deployment of your static content via EdgeOne Pages, leveraging serverless edge functions and key-value storage for fast, reliable delivery. Users can quickly deploy content and receive shareable links, making it ideal for web developers and teams needing easy, scalable web hosting.

about

Tencent EdgeOne Pages is an official MCP server published by tencentedgeone that provides AI assistants with tools and capabilities via the Model Context Protocol. Effortlessly deploy static sites with EdgeOne Pages—an easy, scalable alternative to Amazon website hosting for fast, re It is categorized under cloud infrastructure, productivity. This server exposes 1 tool that AI clients can invoke during conversations and coding sessions.

how to install

You can install Tencent EdgeOne Pages in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server supports remote connections over HTTP, so no local installation is required.

license

MIT

Tencent EdgeOne Pages is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.

readme

EdgeOne Pages MCP

An MCP service for deploying HTML content, folders, or full-stack projects to EdgeOne Pages and obtaining publicly accessible URLs.

<a href="https://glama.ai/mcp/servers/@TencentEdgeOne/edgeone-pages-mcp"> <img width="380" height="200" src="https://glama.ai/mcp/servers/@TencentEdgeOne/edgeone-pages-mcp/badge" alt="EdgeOne Pages MCP server" /> </a>

Demo

Deploy HTML

Deploy Folder

Requirements

  • Node.js 18 or higher

MCP Configuration

stdio MCP Server

Full-featured MCP service that supports the deploy_folder tool for deploying full-stack projects.

// Tencent Cloud International (Default)
{
  "mcpServers": {
    "edgeone-pages-mcp-server": {
      "timeout": 600,
      "command": "npx",
      "args": ["edgeone-pages-mcp-fullstack@latest"]
    }
  }
}

// Tencent Cloud China
{
  "mcpServers": {
    "edgeone-pages-mcp-server": {
      "timeout": 600,
      "command": "npx",
      "args": ["edgeone-pages-mcp-fullstack@latest", "--region", "china"]
    }
  }
}

The following MCP Server will be deprecated soon:

Supports both deploy_html and deploy_folder_or_zip tools.

{
  "mcpServers": {
    "edgeone-pages-mcp-server": {
      "command": "npx",
      "args": ["edgeone-pages-mcp@latest"],
      "env": {
        // Optional. 
        // If you need to deploy folders or zip files to 
        // EdgeOne Pages projects, provide your EdgeOne Pages API token.
        // How to obtain your API token: 
        // https://edgeone.ai/document/177158578324279296
        "EDGEONE_PAGES_API_TOKEN": "",
        // Optional. Leave empty to create a new EdgeOne Pages project.
        // Provide a project name to update an existing project.
        "EDGEONE_PAGES_PROJECT_NAME": ""
      }
    }
  }
}

Streaming HTTP MCP Server

For MCP clients that support HTTP streaming, only supports the deploy_html tool.

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

Tool Details

deploy_html Tool

Architecture Design

EdgeOne Pages MCP Architecture

The architecture diagram shows the complete workflow of the deploy_html tool:

  1. Large Language Model generates HTML content
  2. Content is sent to the EdgeOne Pages MCP Server
  3. MCP Server deploys the content to EdgeOne Pages Edge Functions
  4. Content is stored in EdgeOne KV Store for fast edge access
  5. MCP Server returns a publicly accessible URL
  6. Users can access the deployed content via browser with fast edge delivery

Implementation Details

This tool integrates with EdgeOne Pages Functions to deploy static HTML content:

  1. EdgeOne Pages Functions - A serverless computing platform that supports executing JavaScript/TypeScript code at the edge

  2. Core Implementation Features:

    • Uses EdgeOne Pages KV storage to save and serve HTML content
    • Automatically generates publicly accessible URLs for each deployment
    • Provides comprehensive API error handling and feedback
  3. How It Works:

    • MCP server receives HTML content through the deploy_html tool
    • Connects to EdgeOne Pages API to obtain the base URL
    • Deploys HTML content using the EdgeOne Pages KV API
    • Returns an immediately accessible public URL

For more information, refer to the EdgeOne Pages Functions documentation and EdgeOne Pages KV Storage Guide.

The source code is open source and can be self-deployed with custom domain binding: https://github.com/TencentEdgeOne/self-hosted-pages-mcp

deploy_folder Tool

This tool supports deploying complete projects to EdgeOne Pages:

  • Supports full deployment of static website projects
  • Supports deployment of full-stack applications
  • Option to update existing projects or create new ones

License

MIT

FAQ

What is the Tencent EdgeOne Pages MCP server?
Tencent EdgeOne Pages is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
How do MCP servers relate to agent skills?
Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
How are reviews shown for Tencent EdgeOne Pages?
This profile displays 48 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.7 out of 5—verify behavior in your own environment before production use.

Use Cases

Extended AI Capabilities

Add new capabilities to Claude beyond text generation

Example

Access external data sources, execute code, interact with tools and services

Transform Claude from chatbot to action-taking agent

Context Enhancement

Provide Claude with access to relevant context and data

Example

Load project documentation, access knowledge bases, query databases

Get more accurate, context-aware responses

Workflow Automation

Automate multi-step workflows combining AI and external tools

Example

Research → Summarize → Create document → Send notification

Complete complex tasks end-to-end without manual steps

Implementation Guide

Prerequisites

  • Claude Desktop 0.7.0+ or Cursor IDE with MCP support
  • Basic understanding of MCP architecture and capabilities
  • Access credentials for integrated services (if required)
  • Willingness to experiment and iterate on configuration

Time Estimate

15-60 minutes depending on server complexity

Installation Steps

  1. 1.Install MCP server: npm install -g [package-name] or via GitHub
  2. 2.Add server configuration to ~/.claude/mcp.json
  3. 3.Provide required credentials and configuration
  4. 4.Restart Claude Desktop to load new server
  5. 5.Test basic functionality with simple prompts
  6. 6.Explore capabilities and experiment with use cases
  7. 7.Document successful patterns for reuse

Troubleshooting

  • MCP server not loading: Check config syntax, verify installation
  • Connection errors: Check network, firewall, credentials
  • Feature not working: Read server docs, check required parameters
  • Performance issues: Monitor resource usage, check for network latency
  • Conflicts with other servers: Check port assignments, namespace collisions

Best Practices

✓ Do

  • +Read server documentation thoroughly before setup
  • +Start with simple use cases to validate functionality
  • +Test in non-production environment first
  • +Monitor resource usage and performance
  • +Keep servers updated for bug fixes and new features
  • +Document configuration for team members
  • +Use environment variables for sensitive configuration

✗ Don't

  • Don't grant overly permissive access to MCP servers
  • Don't skip reading security considerations in docs
  • Don't expose sensitive data without proper controls
  • Don't run untrusted MCP servers without code review
  • Don't ignore error messages—investigate root cause

💡 Pro Tips

  • Combine multiple MCP servers for powerful workflows
  • Create custom MCP servers for your specific needs
  • Share successful configurations with team
  • Use MCP inspector for debugging
  • Join MCP community for tips and troubleshooting

Technical Details

Architecture

Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.

Protocols

  • Model Context Protocol (MCP)
  • JSON-RPC 2.0
  • stdio or HTTP transport

Compatibility

  • Claude Desktop
  • Cursor IDE
  • Custom MCP clients

When to Use This

✓ Use When

Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.

✗ Avoid When

Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.

Integration

  • Tool composition: Chain multiple MCP tools in workflows
  • Context augmentation: Provide AI with relevant external data
  • Action delegation: Let AI execute tasks on external systems
  • Bidirectional sync: Keep AI context and external systems in sync

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.

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Ratings

4.748 reviews
  • Harper Dixit· Dec 24, 2024

    According to our notes, Tencent EdgeOne Pages benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.

  • Advait Iyer· Dec 20, 2024

    We wired Tencent EdgeOne Pages into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.

  • Henry Brown· Dec 16, 2024

    Tencent EdgeOne Pages is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.

  • Harper Sethi· Nov 15, 2024

    Tencent EdgeOne Pages has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.

  • Li Kim· Nov 7, 2024

    Strong directory entry: Tencent EdgeOne Pages surfaces stars and publisher context so we could sanity-check maintenance before adopting.

  • Zaid Bansal· Oct 26, 2024

    Useful MCP listing: Tencent EdgeOne Pages is the kind of server we cite when onboarding engineers to host + tool permissions.

  • Amina Iyer· Oct 6, 2024

    Tencent EdgeOne Pages is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.

  • Anika Abbas· Sep 25, 2024

    We wired Tencent EdgeOne Pages into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.

  • Sakshi Patil· Sep 21, 2024

    Tencent EdgeOne Pages reduced integration guesswork — categories and install configs on the listing matched the upstream repo.

  • Li Diallo· Sep 13, 2024

    Strong directory entry: Tencent EdgeOne Pages surfaces stars and publisher context so we could sanity-check maintenance before adopting.

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