SerpApi
SEORun live, structured searches across 15 engines through SerpApi, including Google Search, Maps, News, Scholar, Bing, YouTube, and Amazon. Agents get fully parsed JSON results, re-read archived searches without spending new credits, and monitor account usage.
What This Integration Enables
SerpApi's proposition is that search results are data, not pages: one Search action returns fully parsed JSON from Google Search, Maps, News, Images, Scholar, and Jobs, plus Bing, DuckDuckGo, Yahoo, YouTube, Amazon, eBay, Walmart, Baidu, and Yandex. For a FlowRunner agent that changes what a search is. It stops being a browser task and becomes a queryable input any workflow can branch on: a position, a price, a local pack entry, a news mention. The constraint that shapes every serious SerpApi workflow is the credit pool. Each live Search spends quota; Get Account, Search Locations, and archive reads do not. Well-built agents exploit that asymmetry, and FlowRunner's [human-in-the-loop](/concepts/human-in-the-loop) gate sits exactly where the spending decisions get large. - Track rankings and SERP features across engines, locations, and devices on a schedule - Pull structured product listings from Amazon, eBay, and Walmart searches for pricing work - Re-read archived searches by ID so analysis and retries never re-spend credits - Budget the monthly quota with pre-flight Get Account checks and human sign-off on large batches
Without FlowRunner
With FlowRunner
Use Case Scenarios
Rank tracking that pays for itself in credits saved
An SEO team tracks 400 keywords nightly. The agent calls Get Account first, projects the batch against remaining quota, then loops Search with each keyword, canonical location from Search Locations, and a mobile device profile. Positions and archive IDs land in [Google Sheets](/integrations/google-sheets). When an analyst wants to investigate a drop the next morning, the agent re-reads the exact SERP with Get Search by ID instead of running a fresh query, so the investigation examines the same results the alert was based on and costs nothing.
Marketplace price watch across three retailers
An e-commerce operator monitors 50 products on Amazon, eBay, and Walmart. A twice-daily agent runs Search per product per engine, passing marketplace-specific options through Extra Parameters, and extracts price, seller, and availability from the parsed listings. Changes beyond the margin threshold post to [Slack](/integrations/slack) with the listing linked. When a competitor's price move would trigger a repricing response in the operator's own catalog, that response waits for a merchandiser, because matching a pricing error downward is a mistake you cannot always take back.
Local presence audit for a multi-location business
A franchise operator with 30 locations audits its Google Maps presence monthly. The agent resolves each city with Search Locations to get the canonical location string, runs Search against Google Maps for the service keyword, and records where each location ranks in the local results, and which competitors outrank it. The consolidated report goes to the marketing lead with the locations that fell out of the top results flagged for review, feeding the agency brief with evidence instead of anecdotes.
Human-in-Loop Highlight
Search is the only action in this connector that spends money, and it spends it one query at a time against a finite monthly pool, which is exactly how a mis-scoped loop quietly empties a budget. A keyword list that grows from 400 to 4,000 rows, or a retry branch that re-runs live queries instead of reading the archive, burns quota that cannot be refunded. So FlowRunner agents treat Get Account as a pre-flight check, not a dashboard: before any batch, the agent projects the run's cost against remaining searches, and when the projection crosses the team's budget line, the run pauses and the SEO lead decides: run it whole, trim it, or defer to the reset. The agent also enforces the cheap path by default, reaching for Get Search by ID whenever the question can be answered by a search that already ran. Credits are spent on purpose or not at all.
Agent Capabilities
4 actionsSearch
2- Search Runs a live search against any of 15 engines, including Google Search, Maps, News, Images, Scholar, and Jobs, plus Bing, DuckDuckGo, Yahoo, YouTube, Amazon, eBay, Walmart, Baidu, and Yandex, and returns fully parsed JSON. Common parameters cover query, location, language, country, Google domain, result count, pagination, and device; engine-specific options pass through Extra Parameters. The one action here that consumes a credit.
- Get Search by ID Retrieves the parsed JSON of a previously executed search from the Search Archive by its search ID, within your plan's retention window. The free re-read that keeps analysis, retries, and audits from re-spending quota.
Account
1- Get Account Returns plan name, monthly search quota, searches used, remaining searches and credits, and the hourly rate limit, without consuming a credit. The pre-flight check behind every budgeted batch.
Locations
1- Search Locations Looks up the canonical locations SerpApi supports for the Search operation's Location parameter, with canonical name, GPS coordinates, and approximate reach. Free to call, and the difference between "Springfield" and the Springfield you meant.
Frequently Asked Questions
What can FlowRunner do with SerpApi?
FlowRunner agents can run Search, Get Search by ID, and Get Account in SerpApi, plus 1 more action.
Does connecting SerpApi to FlowRunner require OAuth?
No. SerpApi connects to FlowRunner with an API key, no OAuth flow required.
Can SerpApi trigger a FlowRunner workflow automatically?
SerpApi doesn't currently expose triggers in FlowRunner. It connects as an action step inside workflows started by another trigger.
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