# SERPHouse MCP > SERPHouse MCP grants your agent live access to Google and Bing search engine results pages (SERPs). It scrapes organic search data, dynamic product pricing from shopping tabs, news articles, image sets, and scholarly research across major platforms. ## Overview - **Category:** data-analytics - **Price:** Free - **Tags:** serp-data, proxy-rotation, web-crawling, search-engine-optimization, data-extraction, api-integration ## Description Need your AI client to see what the web actually looks like right now? This MCP gives it direct access to Google and Bing's real-time SERP data. Instead of relying on outdated or general knowledge, your agent can scrape live organic results, track product pricing on Google Shopping, or pull current news headlines from Bing News. The system handles proxy rotation and complex queries so you don't get blocked by search engines. This means your AI doesn't just talk about market trends; it pulls the data backing them up. Whether you need scholarly articles via Google Scholar or video content through Google Videos, this MCP makes that information available to your agent. When you connect SERPHouse via Vinkius, you get one central point of access for all these search capabilities, letting your workflow move from conceptualizing a query to extracting structured data in minutes. ## Tools ### get_account_info Retrieves basic operational details about your SERPHouse account. ### google_news Finds the latest news articles available through Google's search index. ### bing_images Searches Bing for visual content using provided keywords and parameters. ### google_images Searches Google for visual content based on keywords. ### google_scholar Performs focused searches for academic papers and scholarly sources on Google Scholar. ### google_search Executes a general search query across Google, supporting advanced filters like location or language. ### google_shopping Queries Google Shopping to pull product listings and associated dynamic pricing data. ### google_videos Searches for video content available on Google platforms. ### bing_news Retrieves the latest news articles available through Bing's search index. ### bing_search Performs a general web search query across Bing. ### list_locations Provides a list of geographical locations supported for running SERP queries. ## Prompt Examples **Prompt:** ``` Run a targeted Google Scholar query aimed at finding recent papers on 'quantum consciousness theory' focusing on latest available years. ``` **Response:** ``` Deploying `google_scholar`, I aggregated the latest results targeting 'quantum consciousness theory'. The SERP metadata successfully listed major academic journals showcasing papers from Stuart Hameroff with more than 200 distinct citations. ``` **Prompt:** ``` Search Bing News locally from a generic 'United Kingdom' location tag to see the latest headlines on economic metrics. ``` **Response:** ``` Using internal location IDs referencing 'United Kingdom', I checked `bing_news`. There is currently tremendous discussion around new border control metrics influencing local economic exports. I'll summarize the top 10 articles retrieved. ``` ## Capabilities ### Run advanced Google searches It performs standard Google searches while supporting specific parameters like location and language. ### Extract product pricing from shopping results The agent can scrape current product listings and dynamic pricing data directly from Google Shopping. ### Search across multiple media types Your client can query specific content areas like images, videos, news articles (on both Google and Bing), or academic journals. ### Identify supported geographical locations It lists the precise location IDs needed for targeted SERP queries, ensuring regional accuracy. ## Use Cases ### Tracking competitor pricing changes An e-commerce manager needs to monitor if a key competitor is dropping prices. They ask their agent to run google_shopping queries for a specific product category across three different locations, generating a live price comparison matrix. ### Assessing breaking news coverage A PR agency needs instant visibility into how an event is being covered globally. They deploy the agent to run bing_news and google_news for the same keywords, summarizing the top 10 headlines from both sources. ### Conducting academic literature reviews A PhD student needs to find all recent papers on a niche topic. They prompt their agent using google_scholar, instructing it to filter results by publication date and citation count for the last five years. ### General market intelligence gathering A consultant wants a broad understanding of consumer interest in a new product. They use google_search with location parameters to see what consumers are asking about, combining general search data and image results. ## Benefits - Get real-time, actionable data. Instead of relying on what your AI client 'knows,' you get direct access to current search results and live pricing using google_shopping. - Target specific content types easily. Need academic context? Use google_scholar for deep research; need visual evidence? Run a query with google_images or bing_images. - Handle global scope effortlessly. The tool supports location parameters, letting you ask the AI to compare trends between different countries using advanced search capabilities. - Avoid data blockages. This MCP is engineered for proxy rotation, meaning your agent can run complex queries repeatedly without triggering Captcha blocks. - Compare multiple platforms side-by-side. You can query news on both Google News and Bing News in the same workflow to compare coverage instantly. ## How It Works The bottom line is you get real-time web data pulled into your workflow, bypassing static knowledge limitations. 1. First, specify the search engine (Google or Bing) and the content type you want to query—for example, 'shopping' or 'news'. 2. Next, if necessary, provide location parameters or advanced search terms; the MCP uses internal IDs to target specific geographical areas. 3. Finally, your agent executes the request and returns structured data containing the live results, titles, snippets, and metadata. ## Frequently Asked Questions **How does SERPHouse MCP handle geographical location targeting?** It uses specific location IDs. You first call list_locations to get the supported codes, then you pass those identifiers into tools like google_search or bing_search to ensure results are correctly scoped. **Can SERPHouse MCP scrape product data from different retailers?** Yes. By using google_shopping, your agent queries the indexed shopping listings across various platforms, providing dynamic pricing information that changes in real time. **Is this MCP just for general Google searches?** No. It offers specialized tools beyond basic search. You can use google_scholar for academic papers or google_news/bing_news for current events, giving you deep domain access. **What if I need to compare news coverage from Google and Bing?** You simply run two separate calls: one using google_news and another using bing_news. Your agent then aggregates and compares the resulting headlines for you in a single output. **Can SERPHouse MCP handle complex search parameters?** Yes, tools like google_search support advanced filters such as 'location' and 'lang', allowing highly targeted queries that go beyond simple keywords. **How does SERPHouse handle the rotation of IP proxies and blocks?** The SERPHouse API backend completely abstracts the proxy-network infrastructure. Your agent simply supplies queries (e.g., `google_search`), and the API intercepts these actions seamlessly, bouncing globally using elite endpoints to avoid Captchas. **Is the location fetching dynamic? How do I target a specific country search?** Yes. Instruct your AI to retrieve overarching ID bounds leveraging the `list_locations` directory by passing a string fragment. The obtained taxonomy parameter guarantees local precision on your following `google_search` attempts.