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Oxylabs AI studio python mcp server

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Oxylabs AI Studio MCP Server

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📖 Overview

The Oxylabs AI Studio MCP server provides various AI tools for your agents.:

• Scrape: Allows getting content from any url in json or markdown format.
• Crawl: Based on prompt crawls a website and collects data in markdown or json format.
• Browser Agent: Given a task, agent controls a browser to achieve given object and returns data in markdown, json, html or screenshot formats.
• Search: Allows search the web for urls and their contents.

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✅ Prerequisites

Obtain your Api Key from Oxylabs AI Studio dashboard:

Basic Usage

**Python >=3.10+**To run the server best to use uv:

• install it using this guide
• To setup with cursor the easiest way is to use uvx.

cursor uvx

{ "mcpServers": { "oxylabs-ai-studio": { "command": "uvx", "args": ["oxylabs-ai-studio-mcp"], "env": { "OXYLABS_AI_STUDIO_API_KEY": "OXYLABS_AI_STUDIO_API_KEY" } } } }

You can also pull the project and run it locally with uv in cursor:

{ "mcpServers": { "oxylabs-ai-studio": { "command": "uv", "args": [ "--directory", "//oxylabs-ai-studio-mcp", "run", "oxylabs-ai-studio-mcp" ], "env": { "OXYLABS_AI_STUDIO_API_KEY": "OXYLABS_AI_STUDIO_API_KEY" } } } }

Agent example:

import os import asyncio

from pydantic_ai import Agent from pydantic_ai.mcp import MCPServerStdio

server = MCPServerStdio(
'uvx', args=[ 'oxylabs-ai-studio-mcp', ], env={ "OXYLABS_AI_STUDIO_API_KEY": "<your_api_key>", }, )

requires OPENAI_API_KEY to be set.

agent = Agent('openai:gpt-4o', mcp_servers=[server])

async def main():

async with agent.run_mcp_servers():
    result = await agent.run('Got to oxylabs careers page and first first available job and return the job title and description.')
    print(result.output)

if name == "main": asyncio.run(main())

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