# Oxylabs SERP MCP > Oxylabs SERP gives your AI agent direct access to structured search engine data from every major global source. Scrape and parse results—including Google Shopping listings, Bing rankings, Yandex SEO insights, and YouTube video details—without worrying about CAPTCHAs or proxy limits. It turns complex, multi-source market research into a simple prompt. ## Overview - **Category:** data-infrastructure - **Price:** Free - **Tags:** serp-scraping, keyword-tracking, search-engine-data, market-research, structured-data ## Description This MCP connects your AI agent directly to the structured data feeds of the world's leading search engines. You no longer have to open ten different browser tabs and copy-paste results manually. Instead, you tell your agent what kind of data you need—say, product pricing or video views across multiple regions—and it handles the heavy lifting. It pulls clean, structured information from Google Search (organic listings, images, news), Bing, Yandex, Baidu, and YouTube. This means whether you're tracking competitor rankings worldwide or analyzing academic research trends, your agent gets a unified data payload. You can run this MCP through any compatible client like Claude or Cursor; it all connects via Vinkius, the #1 catalog of external services. This lets SEO teams monitor keyword performance across dozens of global domains in minutes. Market researchers use it to check hotel rates on Google Travel or analyze product listings from Google Shopping. The result is clean JSON data ready for analysis, saving hours of manual scraping and ensuring you always have structured, reliable search intelligence. ## Tools ### baidu_search Performs structured search data extraction from Baidu, China's leading search engine. ### bing_search Retrieves automated validation checks and structured results from Microsoft Bing Search. ### google_search Identifies core data records and organic search snippets directly from the Google platform. ### google_images_search Extracts structured metadata about images found during a Google Image search. ### google_news_search Generates JSON payloads containing news articles and headlines from global sources via Google News. ### google_scholar_search Pulls academic search results, publication details, and research paper information from Google Scholar. ### google_shopping_search Retrieves structured product listings, including pricing and availability, from Google Shopping. ### google_travel_search Lists structured rules containing hotel rates and details found on Google Travel. ### yandex_search Performs comprehensive search result data extraction specifically for the Yandex engine. ### youtube_search Identifies video rankings, channel details, and view counts from YouTube searches. ## Prompt Examples **Prompt:** ``` Search Google for 'best enterprise LLMs' and summarize the top organic results. ``` **Response:** ``` Found the top organic results for 'best enterprise LLMs'. 1: Gartner's Magic Quadrant noting OpenAI, Anthropic, and Cohere. 2: Forbes review of private vector RAG implementations. 3: IBM's Granite LLM documentation highlighting data governance. Want me to dive deeper into any of these articles? ``` **Prompt:** ``` Check Google Travel for hotels in Tokyo next weekend. ``` **Response:** ``` Queried google_travel_search for 'hotels in Tokyo'. Returned highly rated results including The Ritz-Carlton Tokyo ($890/night), Shinjuku Washington Hotel ($120/night), and Hotel Gracery Shinjuku ($150/night). Would you like me to filter by rating or specific amenities? ``` **Prompt:** ``` Search YouTube for 'Next.js 15 tutorials'. ``` **Response:** ``` I've pulled the youtube_search results. Top videos are: 1. 'Next.js 15 Crash Course' by Traversy Media (500K views, uploaded 1 mo ago). 2. 'What's new in Next 15?' by Vercel (1.2M views). 3. 'Next.js App Router Masterclass' by Lee Robinson. Want the direct links to these videos? ``` ## Capabilities ### Track global keyword rankings Identify organic search results and rich snippets across multiple international engines like Google, Bing, and Yandex. ### Gather e-commerce product data Extract structured details on products, including pricing and availability from platforms like Google Shopping. ### Analyze video search trends Pull rankings, channel names, view counts, and metadata specifically from YouTube searches. ### Monitor news and academic sources Retrieve structured data from Google News or detailed research papers using Google Scholar. ## Use Cases ### Checking global competitor pricing A market analyst needs to know if a rival's flagship product is cheaper in Brazil or Germany. They ask their agent to run `google_shopping_search` for the product on both local domains, getting structured data points like price and seller name instantly. ### Tracking brand news coverage A PR team needs a daily digest of how their brand is being covered. They prompt their agent to execute `google_news_search` for the last 24 hours, receiving structured data that includes article titles and source domains. ### Assessing video content gaps A digital marketing team wants to see what educational videos are popular in a niche. They run `youtube_search` for 'advanced AI tutorials' and analyze the top results, identifying missing topics or underserved keywords. ### Monitoring competitor hotel rates A travel agency needs real-time pricing data for a key destination. They use `google_travel_search` to check multiple hotels in one query, getting structured JSON with nightly rates and star ratings. ## Benefits - Go beyond simple keyword checks. Use `google_shopping_search` to automatically monitor competitor pricing and product availability across multiple listings. - Save time by running multi-regional analyses. Check the same topic against Google, Bing, and Yandex simultaneously using their respective tools for a full global view. - Analyze content performance instantly. Run searches through `youtube_search` to gather video views, top channels, and metadata without manual effort. - Deepen your research scope. Combine academic findings from `google_scholar_search` with market data from `google_news_search` into one workflow. - Avoid the pain of CAPTCHAs or rate limits. This MCP handles proxy rotation and structured parsing, letting your agent do the dirty work 24/7. ## How It Works The bottom line is you get machine-readable data from complex web pages without ever writing a scraper script. 1. First, connect your AI agent to the MCP by providing your Oxylabs Username and Password. 2. Next, prompt your agent with a specific request, such as 'Find the top 5 results for X on Google Shopping' or 'List the video rankings for Y on YouTube'. 3. The MCP executes the search through the correct tool, returning structured JSON data containing all the requested titles, links, and metadata. ## Frequently Asked Questions **How does Oxylabs SERP handle multiple countries?** It handles global domains by providing dedicated tools. You can use `google_search` for standard Google data, or specialized tools like `baidu_search` and `yandex_search` to target specific regional search engines. **Can I scrape product listings with Oxylabs SERP?** Yes. Use the `google_shopping_search` tool to retrieve structured data on products, including pricing and seller details from Google Shopping. **Is Oxylabs SERP useful for video content analysis?** Absolutely. The dedicated `youtube_search` tool lets you pull key metadata—like view counts, channel names, and top titles—from YouTube search results automatically. **Does this MCP just provide links, or is the data structured?** It provides highly structured JSON payloads. You get parsed snippets, not raw HTML. This makes the data immediately usable by your agent for analysis. **Which tool should I use to check hotel prices?** Use the `google_travel_search` tool. It is specifically designed to enumerate and export structured rules containing active billing and hotel details from Google Travel.