Mcpdatafetchserver
M

Mcpdatafetchserver

The MCP Data Fetch Server is a secure and sandboxed server that fetches web content and extracts data through the Model Context Protocol (MCP) without executing JavaScript.
2.5 points
6.7K

What is MCP Data Fetch Server?

MCP Data Fetch Server is a secure server based on the Model Context Protocol (MCP), specifically designed to fetch content from the Internet. It allows AI assistants (such as Claude, ChatGPT, etc.) to safely access web pages, extract structured data, and download files without exposing the user's system to potential network risks. The server runs in an isolated environment, automatically removing malicious scripts and privacy threats to ensure a secure and efficient data - fetching process.

How to use MCP Data Fetch Server?

Using MCP Data Fetch Server is very simple: First, connect it to an AI assistant that supports MCP (such as LM Studio, Claude Desktop, etc.) through a configuration file. Then, the AI assistant can directly call the tools provided by the server to fetch web content, extract links, download files, etc. You don't need to manually operate the server, and all functions are naturally called through the AI assistant interface.

Use cases

• When an AI assistant needs real - time network information (e.g., getting news, product information, technical documents) • Automated data collection and analysis tasks • Securely downloading network resources (PDFs, images, documents, etc.) • Extracting web page metadata for content summarization • Verifying link availability and status

Main Features

Secure Web Page Fetching
Automatically remove potential threats such as JavaScript, iframes, and cookie pop - ups, and only return clean text content. It supports output in Markdown, plain text, and HTML formats.
Intelligent Data Extraction
Extract structured data such as links, metadata, Open Graph information, and Twitter cards from web pages. It supports filtering by internal links, external links, and resource files.
Secure File Downloading
Download files in an isolated sandbox environment. Automatically check the file type and size (maximum 100MB) to prevent path traversal attacks and malicious file execution.
Built - in Cache System
Automatically cache the fetched content to reduce repeated network requests, improve response speed, and ensure the secure isolation of cached data.
Link Status Check
Quickly check the availability, redirection status, file size, and content type of a URL without downloading the full content.
MCP Protocol Integration
Fully compatible with the Model Context Protocol standard, it can be seamlessly integrated with any AI assistant that supports MCP, providing a standardized tool - calling interface.
Advantages
🔒 Highly secure: Runs in a sandbox environment and automatically filters malicious content
🚀 Ready - to - use: Can be easily integrated with mainstream AI assistants with simple configuration
📊 Rich data: Provides various formats and detailed metadata
⚡ Performance optimized: Built - in cache reduces network latency
🛡️ Comprehensive protection: Prevents common attacks such as prompt injection and path traversal
Limitations
❌ Does not support JavaScript rendering: Cannot fetch dynamic content that depends on JS
📏 File size limit: Maximum 100MB for file downloads and 50MB for web page content
🌐 Network - dependent: Requires a stable Internet connection
🔗 Protocol limitation: Only supports HTTP/HTTPS protocols

How to Use

Install the Server
Clone the project repository and run the installation script. The system will automatically create a Python virtual environment and install the required dependencies.
Configure the AI Assistant
Add the MCP server settings to the configuration file of your AI assistant (such as LM Studio), specifying the server path and working directory.
Start and Use
Restart the AI assistant, and the server will start automatically. Now you can directly request to fetch web content, download files, etc. through the AI assistant interface.

Usage Examples

Research Material Collection
When you need to research a certain topic, let the AI assistant fetch relevant web page content and extract key information.
Link Resource Organization
Organize all relevant resource links in a blog or document for further research or downloading.
Secure File Download
When you need to download documents, images, or other resources from the network, ensure a safe and reliable download process.

Frequently Asked Questions

What's the difference between this server and directly letting an AI access the network?
Which AI assistants are supported?
Can it fetch content from pages that require login?
Where are the downloaded files stored? Are they safe?
If the web page content is very large, will it time out?

Related Resources

GitHub Repository
Project source code and the latest version
Model Context Protocol Documentation
Official specification of the MCP protocol
LM Studio Configuration Guide
How to configure the MCP server in LM Studio
Python Virtual Environment Guide
Tutorial on using Python virtual environments

Installation

Copy the following command to your Client for configuration
{
  "mcpServers": {
    "datafetch": {
      "command": "/absolute/path/to/MCPDataFetchServer.1/run.sh",
      "args": [
        "-d",
        "/absolute/path/to/working/directory"
      ],
      "env": { "WORKING_DIR": "." }
    }
  }
}
Note: Your key is sensitive information, do not share it with anyone.

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