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oxylabs-mcp

MCP.Pizza Chef: oxylabs

The Oxylabs MCP Server enables seamless access to web data through the Model Context Protocol, allowing LLMs to interact with real-time web data sources securely and efficiently. It acts as a bridge between Oxylabs' extensive web data infrastructure and MCP clients, facilitating structured, real-time context feeding into language models for enhanced AI workflows and automation.

Use This MCP server To

Access real-time web data within LLM workflows Integrate Oxylabs web scraping into AI applications Enable LLMs to query structured web data Automate data extraction from websites via MCP Combine web data with other context sources for AI reasoning Use Oxylabs data for market research and analysis Feed live web content into chatbots or virtual assistants

README

Oxylabs + MCP

Oxylabs MCP Server

Access web data seamlessly with Oxylabs via the Model Context Protocol

📖 Overview

The Oxylabs MCP server provides a bridge between AI models and the web. It enables them to scrape any URL, render JavaScript-heavy pages, extract and format content for AI use, bypass anti-scraping measures, and access geo-restricted web data from 195+ countries.

This implementation leverages the Model Context Protocol (MCP) to create a secure, standardized way for AI assistants to interact with web content.

✨ Key Features

Scrape content from any site
  • Extract data from any URL, including complex single-page applications
  • Fully render dynamic websites using headless browser support
  • Choose full JavaScript rendering, HTML-only, or none
  • Emulate Mobile and Desktop viewports for realistic rendering
Automatically get AI-ready data
  • Automatically clean and convert HTML to Markdown for improved readability
  • Use automated parsers for popular targets like Google, Amazon, and etc.
Bypass blocks & geo-restrictions
  • Bypass sophisticated bot protection systems with high success rate
  • Reliably scrape even the most complex websites
  • Get automatically rotating IPs from a proxy pool covering 195+ countries
Flexible setup & cross-platform support
  • Set rendering and parsing options if needed
  • Feed data directly into AI models or analytics tools
  • Works on macOS, Windows, and Linux
Built-in error handling and request management
  • Comprehensive error handling and reporting
  • Smart rate limiting and request management

💡 Example Queries

When you've set up the MCP server with Claude, you can make requests like:

  • Could you scrape https://www.google.com/search?q=ai page?
  • Scrape https://www.amazon.de/-/en/Smartphone-Contract-Function-Manufacturer-Exclusive/dp/B0CNKD651V with parse enabled
  • Scrape https://www.amazon.de/-/en/gp/bestsellers/beauty/ref=zg_bs_nav_beauty_0 with parse and render enabled
  • Use web unblocker with render to scrape https://www.bestbuy.com/site/top-deals/all-electronics-on-sale/pcmcat1674241939957.c

✅ Prerequisites

Before you begin, make sure you have:

  • Oxylabs Account: Obtain your username and password from Oxylabs (1-week free trial available)

Basic Usage

Via Smithery CLI:

  • Node.js (v16+)
  • npx command-line tool

Via uv:

  • uv package manager – install it using this guide

Local/Dev Setup

  • Python 3.12+
  • uv package manager – install it using this guide

🧩 API Parameters

The Oxylabs MCP server supports these parameters:

Parameter Description Values
url The URL to scrape Any valid URL
parse Enable structured data extraction True or False
render Use headless browser rendering html or None

⚙️ Basic Setup Instructions

Install via Smithery

Automatically install Oxylabs MCP server via Smithery:

npx -y @smithery/cli install @oxylabs/oxylabs-mcp --client <client>

List of clients supported by Oxylabs at the moment:

  • claude
  • cursor

Manual MCP configuration options

  1. Config with uvx. Will install the CLI client and Oxylabs MCP server that performs calls directly to the Oxylabs API. Recommended and the most stable option at the moment.

    {
      "mcpServers": {
        "oxylabs_scraper_uvx": {
          "command": "uvx",
          "args": [
            "oxylabs-mcp"
          ],
          "env": {
            "OXYLABS_USERNAME": "OXYLABS_USERNAME",
            "OXYLABS_PASSWORD": "OXYLABS_PASSWORD"
          }
        }
      }
    }
  2. Config with npx. Will install the Smithery CLI client that performs calls to the Oxylabs MCP server hosted in Smithery.

    {
      "mcpServers": {
        "oxylabs-mcp": {
          "command": "npx",
          "args": [
            "-y",
            "@smithery/cli@latest",
            "run",
            "@oxylabs/oxylabs-mcp",
            "--config",
            "\"{\\\"oxylabsUsername\\\":\\\"OXYLABS_USERNAME\\\",\\\"oxylabsPassword\\\":\\\"OXYLABS_PASSWORD\\\"}\""
          ]
        }
      }
    }
  3. Config with uv. Will install CLI client and Oxylabs MCP server that references the local code. For the local development.

    {
      "mcpServers": {
        "oxylabs_scraper": {
          "command": "uv",
          "args": [
            "--directory",
            "/<Absolute-path-to-folder>/oxylabs-mcp",
            "run",
            "oxylabs-mcp"
          ],
          "env": {
            "OXYLABS_USERNAME": "OXYLABS_USERNAME",
            "OXYLABS_PASSWORD": "OXYLABS_PASSWORD"
          }
        }
      }
    }

Note

If you don't have uvx utility you need to install it first with brew install uv

Tip

If you run into errors with uvx, try using the full path to uvx in the command field. For example, /Users/my-user/.local/bin/uvx. If you are using Windows and experiencing issues with Cursor, refer to the guidelines described here.

Manual Setup with Claude Desktop

Navigate to Claude → Settings → Developer → Edit Config and add one of the configurations above to the claude_desktop_config.json file.

Manual Setup with Cursor AI

Navigate to Cursor → Settings → Cursor Settings → MCP. Click Add new global MCP server and add one of the configurations above.


💻 Local/Dev Setup Instructions

Clone repository

git clone <git:url>

Install dependencies

Install MCP server dependencies:

cd mcp-server-oxylabs

# Create virtual environment and activate it
uv venv

source .venv/bin/activate # MacOS/Linux
# OR
.venv/Scripts/activate # Windows

# Install dependencies
uv sync

🐞 Debugging

make run

Then access MCP Inspector at http://localhost:5173. You may need to add your username and password as environment variables in the inspector under OXYLABS_USERNAME and OXYLABS_PASSWORD.


License

This project is licensed under the MIT License.

About Oxylabs

Established in 2015, Oxylabs is a market-leading web intelligence collection platform, driven by the highest business, ethics, and compliance standards, enabling companies worldwide to unlock data-driven insights.

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oxylabs-mcp FAQ

How do I install the Oxylabs MCP Server?
You can install it via PyPI using 'pip install oxylabs-mcp', with detailed instructions on the GitHub repository.
What authentication methods does Oxylabs MCP support?
It supports API key-based authentication to securely access Oxylabs web data services.
Can Oxylabs MCP Server handle large-scale web data requests?
Yes, it is designed to efficiently manage high-volume data queries with Oxylabs' infrastructure.
How does Oxylabs MCP ensure data freshness?
It accesses live web data through Oxylabs proxies, ensuring up-to-date information is provided to the model.
Is the Oxylabs MCP Server compatible with multiple LLM providers?
Yes, it works with any MCP client and supports models like OpenAI, Anthropic Claude, and Google Gemini.
How do I configure Oxylabs MCP Server for custom web data sources?
Configuration options allow specifying target domains and scraping parameters via the server's settings.
What security measures are in place for Oxylabs MCP?
It uses scoped API keys and secure communication channels to protect data and access.
Where can I find support or community help for Oxylabs MCP?
Support is available via the official Discord server and GitHub issues page.