How to get Google AI Overviews and AI Mode answers as JSON

A developer has released AnswerLine, an API that returns Google AI Overviews and AI Mode answers as structured JSON, including the answer text, cited sources with positions, and the secondary search queries AI Mode fans out to. The service also parses classic Google SERPs with any AI Overview attached, and the developer recommends a weekly workflow of querying ~50 buyer-intent prompts per surface and diffing the cited sources week over week to see which pages win citations.

Google AI Overviews now answer a large share of commercial queries, and AI Mode is rolling out as a full conversational search surface. If you track SEO, brand mentions or competitor positioning, the answer text and the citations inside those AI blocks matter more than the ten blue links under them. The problem: there is no official API for either surface. Here is how I get AI Overview and AI Mode answers as structured JSON, and what the data actually looks like. A classic organic result is a ranked list of URLs. An AI Overview is different: If your content is cited in position 1 of the Overview, the organic rank below it is almost irrelevant. If a competitor is cited and you are not, no amount of position-3 organic rankings fixes that. I'm using AnswerLine https://answerline.dev/engines/ai-mode/ — an API I work on that serves both surfaces plus ChatGPT, Gemini, Copilot and Google News through one contract. An async task per surface: curl -X POST https://api.answerline.dev/v1/async/task \ -H "Authorization: Bearer $ANSWERLINE KEY" \ -H "Content-Type: application/json" \ -d '{ "taskType": "AIMODE", "input": { "prompt": "best rank tracker for local SEO", "country": "US" } }' Poll GET /v1/async/task/{id} or set a webhook , and you get back: { "answer": "...", "sources": { "url": "https://...", "position": 1, "label": "..." } , "searchQueries": "local rank tracker", "rank tracker for agencies" } The searchQueries field is the underrated part: AI Mode's fan-out shows you the secondary queries the model thinks matter — that is a keyword-research surface nobody had two years ago. taskType: "GOOGLE SEARCH" returns the classic SERP parsed organic, ads, PAA, related searches, knowledge graph with the AI Overview attached when Google renders one — one response covering both eras of the results page. -d '{ "taskType": "GOOGLE SEARCH", "input": { "q": "ai visibility tracking", "country": "DE" } }' Google's AI surfaces are the most aggressively bot-protected pages they serve, and the markup changes weekly. The cost structure that worked for scraping organic results cheap proxies + selectors does not survive AI Mode. We run the collection layer so the response shape stays stable; failed calls are not charged. A weekly job: for each of ~50 buyer-intent prompts in your category, fire one task per surface, store answer , sources and country , then diff week over week. When the cited set changes, you see exactly which source won the citation — and can go write better content than it. That is the entire workflow: ask, store, diff, out-write the cited page. Free tier is 500 credits at dashboard.answerline.dev https://dashboard.answerline.dev , no card. Docs are at answerline.dev/docs https://answerline.dev/docs .