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
7.2K

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.

Alternatives

R
Rsdoctor
Rsdoctor is a build analysis tool specifically designed for the Rspack ecosystem, fully compatible with webpack. It provides visual build analysis, multi - dimensional performance diagnosis, and intelligent optimization suggestions to help developers improve build efficiency and engineering quality.
TypeScript
9.0K
5 points
N
Next Devtools MCP
The Next.js development tools MCP server provides Next.js development tools and utilities for AI programming assistants such as Claude and Cursor, including runtime diagnostics, development automation, and document access functions.
TypeScript
8.7K
5 points
T
Testkube
Testkube is a test orchestration and execution framework for cloud-native applications, providing a unified platform to define, run, and analyze tests. It supports existing testing tools and Kubernetes infrastructure.
Go
6.4K
5 points
M
MCP Windbg
An MCP server that integrates AI models with WinDbg/CDB for analyzing Windows crash dump files and remote debugging, supporting natural language interaction to execute debugging commands.
Python
10.0K
5 points
R
Runno
Runno is a collection of JavaScript toolkits for securely running code in multiple programming languages in environments such as browsers and Node.js. It achieves sandboxed execution through WebAssembly and WASI, supports languages such as Python, Ruby, JavaScript, SQLite, C/C++, and provides integration methods such as web components and MCP servers.
TypeScript
7.7K
5 points
P
Praisonai
PraisonAI is a production-ready multi-AI agent framework with self-reflection capabilities, designed to create AI agents to automate the solution of various problems from simple tasks to complex challenges. It simplifies the construction and management of multi-agent LLM systems by integrating PraisonAI agents, AG2, and CrewAI into a low-code solution, emphasizing simplicity, customization, and effective human-machine collaboration.
Python
6.5K
5 points
N
Netdata
Netdata is an open-source real-time infrastructure monitoring platform that provides second-level metric collection, visualization, machine learning-driven anomaly detection, and automated alerts. It can achieve full-stack monitoring without complex configuration.
Go
8.7K
5 points
M
MCP Server
The Mapbox MCP Server is a model context protocol server implemented in Node.js, providing AI applications with access to Mapbox geospatial APIs, including functions such as geocoding, point - of - interest search, route planning, isochrone analysis, and static map generation.
TypeScript
7.9K
4 points
M
Markdownify MCP
Markdownify is a multi-functional file conversion service that supports converting multiple formats such as PDFs, images, audio, and web page content into Markdown format.
TypeScript
30.8K
5 points
N
Notion Api MCP
Certified
A Python-based MCP Server that provides advanced to-do list management and content organization functions through the Notion API, enabling seamless integration between AI models and Notion.
Python
18.6K
4.5 points
G
Gitlab MCP Server
Certified
The GitLab MCP server is a project based on the Model Context Protocol that provides a comprehensive toolset for interacting with GitLab accounts, including code review, merge request management, CI/CD configuration, and other functions.
TypeScript
22.4K
4.3 points
D
Duckduckgo MCP Server
Certified
The DuckDuckGo Search MCP Server provides web search and content scraping services for LLMs such as Claude.
Python
64.8K
4.3 points
U
Unity
Certified
UnityMCP is a Unity editor plugin that implements the Model Context Protocol (MCP), providing seamless integration between Unity and AI assistants, including real - time state monitoring, remote command execution, and log functions.
C#
27.5K
5 points
F
Figma Context MCP
Framelink Figma MCP Server is a server that provides access to Figma design data for AI programming tools (such as Cursor). By simplifying the Figma API response, it helps AI more accurately achieve one - click conversion from design to code.
TypeScript
57.9K
4.5 points
M
Minimax MCP Server
The MiniMax Model Context Protocol (MCP) is an official server that supports interaction with powerful text-to-speech, video/image generation APIs, and is suitable for various client tools such as Claude Desktop and Cursor.
Python
43.5K
4.8 points
C
Context7
Context7 MCP is a service that provides real-time, version-specific documentation and code examples for AI programming assistants. It is directly integrated into prompts through the Model Context Protocol to solve the problem of LLMs using outdated information.
TypeScript
87.5K
4.7 points
AIBase
Zhiqi Future, Your AI Solution Think Tank
© 2026AIBase