mcp-server-fetch-typescript MCP Server: Universal Web Content Fetching and Conversion

Overview: What is mcp-server-fetch-typescript MCP Server?

Mcp-server-fetch-typescript is a Model Context Protocol (MCP) server designed to facilitate efficient web content fetching and conversion for AI applications. It provides robust capabilities for extracting, rendering, and converting various types of web resources into formats suitable for integration with AI workflows. By adhering to the standardized protocol defined by MCP, it ensures seamless connectivity between AI applications like Claude Desktop, Continue, Cursor, and other MCP clients, as well as diverse data sources.

🔧 Core Features & MCP Capabilities

Tools Overview

get_raw_text

This tool retrieves raw text content from URLs directly. It is ideal for scenarios where uncached, unprocessed text-based resources are needed.

• Parameters: Requires a url parameter pointing to the target resource.
• Output: Returns unprocessed text content without browser rendering.
• Compatibility: Supports JSON, XML, CSV, TSV, or plain text files.

get_rendered_html

Designed for fetching and returning fully rendered HTML content after JavaScript execution. This tool is essential for modern web applications and single-page applications (SPAs) where client-side scripts are crucial.

• Parameters: Requires a url parameter pointing to the target URL.
• Output: Returns complete, rendered HTML content.
• Implementation: Utilizes Playwright for headless browser rendering.

get_markdown

This tool converts web content into Markdown format. It is particularly useful for archiving and documenting structured content with formats that support tables and definition lists.

• Parameters: Requires a url parameter pointing to the target resource.
• Output: Returns well-formatted Markdown content, preserving structural elements.
• Use Cases: Suitable for content archiving, documentation of articles, and blog posts.

get_markdown_summary

Automatically extracts main content from web pages and converts it into clean, concise Markdown. This tool removes navigation and extraneous headers, feeters, etc., to focus on the core of the content.

• Parameters: Requires a url parameter pointing to the target resource.
• Output: Returns cleaned-up, focused Markdown content.

⚙️ MCP Architecture & Protocol Implementation

Protocol Flow Diagram

The mcp-server-fetch-typescript implements Model Context Protocol (MCP) for seamless integration with various AI clients. The protocol flow is structured as follows:

graph TD
    A[AI Application] -->|MCP Client| B[MCP Protocol]
    B --> C[MCP Server]
    C --> D[Data Source/Tool]
    style A fill:#e1f5fe
    style C fill:#f3e5f5
    style D fill:#e8f5e8

Client Compatibility Matrix

The mcp-server-fetch-typescript is compatible with multiple MCP clients, as demonstrated in the following matrix:

MCP Client	Resources	Tools	Prompts	Status
Claude Desktop	✅	✅	✅	Full Support
Continue	✅	✅	✅	Full Support
Cursor	❌	✅	❌	Tools Only

🚀 Getting Started with Installation

As a Global Package

To install mcp-server-fetch-typescript as a global package, execute the following command:

npm install -g mcp-server-fetch-typescript

Alternatively, you can add it as a project dependency using:

npm install mcp-server-fetch-typescript

Debugging and Inspection

For debugging purposes, use the MCP server inspector tool. The commands are provided below:

Using npx to debug:

npx @modelcontextprotocol/inspector npx -y mcp-server-fetch-typescript

Or run directly with Node.js:

npx @modelcontextprotocol/inspector node /path/to/mcp-server-fetch-typescript/build/index.js

💡 Key Use Cases in AI Workflows

Real-Time Data Extraction for Research

A university researcher needs to extract real-time data from multiple websites for academic research. Using mcp-server-fetch-typescript, she can efficiently fetch and process live web content through MCP clients like Claude Desktop or Continue.

graph LR
    A[AI Application (Claude Desktop/Continue)] --> B[Request Web Content]
    B --> C[MCP Protocol]
    C --> D[MCP Server - mcp-server-fetch-typescript]
    D --> E[Extract Data from Web Source(s)]
    style A fill:#f3e5f5
    style D fill:#e8f5e8

Automated Content Archiving for Documentation

A tech company is documenting its product suite based on user feedback and support tickets. The team uses mcp-server-fetch-typescript to archive relevant content from multiple websites in a structured format using the get_markdown tool.

🔌 Integration with MCP Clients

To integrate mcp-server-fetch-typescript into an AI application like Claude Desktop, follow these steps:

1. Add Server Config:
   • On MacOS:

     "mcpServers": {
       "mcp-server-fetch-typescript": {
         "command": "npx",
         "args": [
           "-y",
           "mcp-server-fetch-typescript"
         ]
       }
     }
     

   • On Windows:

     "mcpServers": {
       "mcp-server-fetch-typescript": {
         "command": "node",
         "args": [
           "/path/to/mcp-server-fetch-typescript/build/index.js"
         ]
       }
     }
     

📊 Performance & Compatibility Matrix

The mcp-server-fetch-typescript has been rigorously tested across multiple MCP clients. Here’s a performance and compatibility summary:

Performance Metrics

• Response Time: Average response time is 3 seconds for rendering complex web pages.
• Resource Consumption: Optimal resource consumption with minimal impact on the server.

Compatibility Summary

• Claude Desktop: Full support for all tools with high throughput.
• Continue: High compatibility; minor adjustments required for certain features.
• Cursor: Limited functionality due to client constraints, primarily supports tool integration.

🛠️ Advanced Configuration & Security

For advanced users and administrators, detailed configuration is necessary. The following are critical security measures:

Environment Variables

{
  "mcpServers": {
    "[server-name]": {
      "command": "npx",
      "args": ["-y", "@modelcontextprotocol/server-[name]"],
      "env": {
        "API_KEY": "your-api-key"
      }
    }
  }
}

Security Practices

• Authentication: Implement API keys and secure tokens to protect against unauthorized access.
• Rate Limiting: Set rate limits on HTTP requests to prevent abuse.

❓ Frequently Asked Questions (FAQ)

1. Q: Can mcp-server-fetch-typescript handle SSL errors?

   • A: Yes, it can handle SSL errors using appropriate configuration settings. Ensure that the client and server environments are properly configured for secure connections.

2. Q: Is there a way to limit bandwidth usage during peak times?

   • A: Yes, by configuring rate limiting in the MCP protocol, you can manage bandwidth effectively even during peak traffic periods.

3. Q: How do I troubleshoot issues when using mcp-server-fetch-typescript with Continue?

   • A: Check the logs and error messages provided by the server for clues. Ensure that all dependencies are up to date and that the client version is compatible.

4. Q: Is there a performance difference between get_raw_text and get_rendered_html tools?

   • A: get_raw_text operates faster but doesn’t support complex web rendering, while get_rendered_html offers comprehensive content extraction at the cost of some processing time.

5. Q: How do I integrate custom data sources or tools with mcp-server-fetch-typescript?

   • A: Customize the server by extending or modifying the existing functionalities to support additional data sources and tools as needed.

👨‍💻 Development & Contribution Guidelines

Contributions are welcome! Here’s how you can help:

1. Fork the Repository: Go to the GitHub repository and fork it.
2. Report Issues: Use the issue tracker for reporting bugs or requesting new features.
3. Contribute Code: Submit pull requests with well-documented changes.

🌐 MCP Ecosystem & Resources

The mcp-server-fetch-typescript is part of a broader ecosystem that includes other MCP servers and tools designed to enhance AI application development. For more information, visit the Model Context Protocol website or join relevant communities for support and collaboration.

By leveraging the capabilities of mcp-server-fetch-typescript, developers can significantly streamline their workflows and improve the functionality of AI applications by integrating robust web content management directly into their tools and processes.