# ValueSERP MCP > ValueSERP brings live, structured data from Google Search directly into your AI agent. It lets you programmatically query organic results, find local business details via Google Places, scrape product pricing from Shopping, and pull academic abstracts from Scholar—all while bypassing common CAPTCHAs and blocks. ## Overview - **Category:** data-analytics - **Price:** Free - **Tags:** serp-data, search-engine-optimization, data-extraction, market-research, google-search, api-parsing ## Description Your AI client suddenly has eyes on the live internet. Instead of relying on static knowledge cutoffs, this MCP connects your agent to real-time web intelligence. You can run complex queries against Google Organic, Images, News, Videos, and Scholar, getting structured data for everything from market research to academic literature reviews. Need to check a competitor's local rating or track product price shifts? Use the dedicated tools to pull raw Google Shopping and Places data directly into your conversation flow. The value is that you don't just get search links; you get usable, parseable data—all managed through Vinkius, so you can connect this power source to any compatible agent. Your AI client becomes a robust, unblockable intelligence engine for live web research. ## Tools ### custom_serp_search Runs a highly customized Google search query using advanced, specific parameters. ### get_search_suggestions Pulls the most likely continuations for text input based on real-time Google autocomplete data. ### google_image_search Performs a search and returns direct, usable URLs to relevant images found on Google. ### google_news_search Searches for recent news articles and reports available through the Google News platform. ### google_search Conducts a standard organic search query on Google, providing basic results with optional location context. ### google_places_search Locates and retrieves detailed information for specific local businesses or points of interest on Google Maps. ### google_scholar_search Finds scholarly articles, authors, and abstracts specifically within the Google Scholar database. ### google_shopping_search Collects product names, current prices, and links for items found on Google Shopping. ### google_video_search Searches for video content across YouTube and other platforms via the Google Video search tool. ### get_related_questions Extracts 'People Also Ask' questions and potential answers to better understand user query depth. ## Prompt Examples **Prompt:** ``` Search Google Scholar for recent papers on 'quantum computing error correction'. ``` **Response:** ``` Here are the top results from Google Scholar for 'quantum computing error correction'. I found 8 highly-cited abstracts in the first page. For instance, 'Surface codes: Towards practical large-scale quantum computation' by Fowler et al. Would you like me to extract the citations count and PDF links for all of them? ``` **Prompt:** ``` Find the top business ratings for 'pizza places in Chicago' using Google Places. ``` **Response:** ``` I've pulled the local pack from Google Places for 'pizza places in Chicago'. The top-rated spots are Lou Malnati's Pizzeria (4.6 stars, 12,304 reviews), Giordano's (4.5 stars), and Pequod's Pizza (4.6 stars). Below is a table with their addresses, exact GPS coordinates, and current open/closed status. ``` **Prompt:** ``` Check Google Autocomplete suggestions when someone types 'how to start a'. ``` **Response:** ``` Based on real-time Google Autocomplete, the most frequent continuations for 'how to start a' are currently: 'business', 'clothing brand', 'llc', 'conversation', 'cover letter', and 'nonprofit'. These reflect high-volume search intents. Let's dig into 'clothing brand' if you'd like to do further research on that vertical. ``` ## Capabilities ### Execute general Google searches Perform standard programmatic queries across Google Organic results with optional location targeting. ### Analyze local business data Find specific details, ratings, and coordinates for physical locations using the Google Places tool. ### Scrape product market data Retrieve product names, current prices, and merchant links from Google Shopping results. ### Research academic papers Search for scholarly publications and extract their abstracts directly from Google Scholar. ### Understand search intent Retrieve predictive suggestions or 'People Also Ask' snippets to map out user research paths. ## Use Cases ### Need to check if a new product idea has immediate market interest? A growth marketer uses the agent to run several searches. First, they use `get_related_questions` on their core topic. Then, they use `google_shopping_search` to see what pricing models competitors are using right now. This combination provides a full picture of both user curiosity and market readiness. ### Building a content cluster around an academic field. A researcher asks the agent for foundational papers on 'quantum computing'. The agent uses `google_scholar_search` to pull 10 abstracts. It then uses `get_related_questions` to find adjacent topics, mapping out a complete research pipeline. ### Comparing local service providers in a new city. An SEO analyst needs to know the top three plumbers in Austin. They use `google_places_search` with specific coordinates and business names. The result gives them structured data including ratings, addresses, and current operating hours. ### Understanding shifts in trending search topics. A marketing team wants to know what's hot right now. They use `get_search_suggestions` with a general query like 'how to start a...' to see the most popular continuations, immediately informing their content calendar. ## Benefits - You stop guessing about what users are searching for. By running `get_related_questions`, you pull the exact 'People Also Ask' snippets and questions, letting you build content around confirmed user intent. - Competitor analysis gets fast. Use `google_shopping_search` to quickly benchmark product prices and find out which merchants dominate specific niches across different regions. - Academic research accelerates immediately. Running `google_scholar_search` lets your agent pull abstracts from top papers, letting you synthesize complex literature reviews without manual searching. - Local market analysis becomes precise. The `google_places_search` tool gives you live ratings and GPS coordinates for any business, making it perfect for physical location strategy. - You eliminate data gaps. Instead of relying on old training data, this MCP streams fresh information from Google News, Images, or videos using dedicated tools like `google_news_search`. ## How It Works The bottom line is that your agent gets real-time web results—not just text, but actionable, formatted data ready for analysis. 1. Subscribe to the ValueSERP MCP and enter your unique API key into Vinkius. 2. Your agent calls a specific function within the MCP, passing in parameters like keywords or location bounds. 3. The MCP executes the complex search query against Google's infrastructure and returns structured JSON data directly back to your AI client. ## Frequently Asked Questions **How does ValueSERP MCP handle CAPTCHAs?** The MCP is built to bypass common blocking mechanisms. It handles complex parsing and structured data retrieval so your agent doesn't get stuck on typical CAPTCHA walls. **Can I use the ValueSERP MCP for e-commerce research?** Yes, absolutely. Use `google_shopping_search` to pull product names, current prices, and merchant links, allowing you to benchmark competitor offerings instantly. **Does this MCP only work with Google Search? Can I search other sites?** This MCP is focused on extracting structured data from Google's ecosystem (Search, Places, Scholar, etc.). It specializes in making that specific web data available to your agent. **How do I find local competitor ratings using ValueSERP MCP?** Use the `google_places_search` tool. You just provide a place name and location, and it returns structured data including star ratings, review counts, and GPS coordinates. **Is this suitable for my own internal company data?** No. This MCP is designed to pull real-time information from the public Google web index. It cannot access or query private documents or proprietary databases.