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Build AI Search Engines with Scrapingdog APIs

Your model's knowledge stops at its training cutoff. The web doesn't. Pull live results from Google, Bing, and Brave, fetch the full page behind any link as clean Markdown, and give every answer a source it can actually cite.

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Explore how Scrapingdog’s APIs can power AI search engines

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Ground LLM Answers in Real-Time Search Results

On its own, a model is guessing about anything that happened after its training cutoff. Send the user's question to our search APIs, drop the results into the prompt, and the answer is built on what's on the web today, with links your users can check.

  • Organic results come back as clean JSON, with the title, link, and snippet already separated, so there's nothing to parse before it goes into a prompt.
  • Add Bing or Brave Search when you want more than one engine's take on a topic.
  • Set the country and language to match where the question is being asked from.
Documentation:
  • Google Search API
  • Bing Search API
  • Brave Search API
Google search results for "football" next to the matching organic_results JSON from the Google Search API

Turn Any Web Page into LLM-Ready Content

A snippet is two lines of text, and your model usually needs the whole page. Point the Web Scraping API at any result and you get the content back ready to use, with no HTML to clean up first.

  • Use formats=markdown to get the page as clean Markdown, or formats=summary for a shorter version when context space is tight.
  • Ask the page a question with ai_query, or use ai_extract_rules to pull out only the fields you need.
  • We handle JavaScript rendering and proxy rotation, so pages built with React or Vue come back fully loaded.
Documentation:
  • Web Scraping API
  • AI extraction parameters
The Scrapingdog homepage returned as Markdown by the Web Scraping API with formats=markdown

See How Google’s AI Answers the Same Question

If you're building an answer engine, Google AI Mode is what people will compare you to. The Google AI Mode API gives you its answer as structured text blocks, along with the pages it cited, so you can put the two side by side.

  • Run your test queries through both and see where your answers differ.
  • Check which sources Google cites, and whether your retrieval finds the same ones.
  • Use the Universal Search API to see how results for the same query change across search engines.
Documentation:
  • Google AI Mode API
  • Universal Search API
Google AI Mode answer for "scrapingdog" next to the text_blocks and references JSON from the Google AI Mode API

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Frequently Asked Questions

  • Answer engines, research assistants, RAG pipelines, and AI agents that need to know what’s on the web right now. Our search APIs give you live results from Google, Bing, and Brave, and the Web Scraping API gets you the full content of any page in a format your model can read.

  • Send the user’s question as the query to the Google Search API, then pass the titles, snippets, and links it returns to your model as context. The answer is then based on current sources, and you can show those links as citations.

  • Yes. Call the Web Scraping API with formats=markdown to get the page as clean Markdown, or formats=summary for a shorter version. If you only need a few details, use ai_query or ai_extract_rules to pull out just those.

  • You can use others. There are dedicated Bing Search and Brave Search APIs, and the Universal Search API covers results from multiple search engines.

  • Yes. Every API returns structured JSON that an agent can call as a tool, and our SDKs and MCP server are on the SDKs & MCP Server page.

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