SEO tools

"find keywords for X", "what should I target around X", "keyword ideas for a page about X".

• Metrics on keywords the user already has, use seo_get_keyword_metrics (this tool already returns those metrics, so do not call it afterwards).
• Prompts people ask AI engines, use aeo_search_prompts.
• The top-10 page for one query, use seo_get_serp.

A list. Each row has keyword, volume, kd (0 to 100), intent, cpc (USD), competition, bid_low, bid_high (Google Ads top-of-page bid range, USD), trend[12] (month, volume). volume, kd, cpc null = provider has no data; 0 = measured zero.

5 + 5 per 100 rows. Default 100 rows = 10 credits. Cached 7 days.

The user supplies keywords, or you need numbers for a list from elsewhere. ai_volume true when the question is how often AI engines see the keyword.

• Discovering keywords, use seo_search_keywords (it already includes these metrics, do not call this after it).
• AI-engine prompts, use aeo_search_prompts.
• Checking rankings, use seo_get_position.

A list. Each row has keyword, volume, kd, intent, cpc, competition, bid_low, bid_high (Google Ads top-of-page bid range, USD), trend[12], ai_volume, ai_trend[12]. One row per input keyword in the order given. volume/kd null = provider has no data; 0 = measured zero. With source google_ads, kd and intent are always null and keywords over 80 characters come back all null. ai_volume and ai_trend are null unless ai_volume is true.

5 + 5 per 100 keywords with source labs; 24 flat with source google_ads; ai_volume adds 4 + 4 per 100 keywords. Default 100 keywords = 10 credits. Cached 7 days.

"what ranks for X", "who is on page one for X", "is there a featured snippet or AI overview for X".

• Where one site ranks for a keyword, use seo_get_position (it scans the top 100 for you).
• Keyword ideas, use seo_search_keywords.
• The businesses Google Maps ranks for a local search, use maps_search_places.

One record with features[] (featured_snippet, people_also_ask, video, ai_overview and others), results[] (rank, organic_rank, type, url, domain, title, snippet, published_at, rating), related_searches[], ai_overview (text, references[]) or null, results_count, check_url. depth counts organic rows: the default returns 10 organic results whenever Google has them, with the features ranked among them on top. Each People Also Ask question and each forum thread is its own row at its block's rank; for a question, title is the question and snippet the answer, url null when Google's answer is an AI overview. domain is null on a row whose url is still a google.com/goto redirect. location localises the local pack, not the organic rows of a bare service search: put the town in the keyword ("dentist columbus ohio") for local organic results. Paid ads seldom come back, so the page says nothing about who bids on the query; a named rival's search ads are in ads_get_advertiser_ads with platform google.

1 credit per 10 results, +1 with ai_overview. Default top 10 = 1 credit. Cached 24 hours.

"where does example.com rank for X", "did we make page one for X", a rank check for a handful of keywords.

• Every keyword a domain ranks for, use seo_get_ranked_keywords.
• The full page-one list, use seo_get_serp.
• Tracking over time: monitoring_create_monitor with google_rankings.

One record with keyword, target, rank (absolute, null when not in the top 100), organic_rank, url, title, scanned_depth, above[] (rank, domain, url of the organic results just ahead, at most 10, nearest last). For a local business, location does not localise the organic rank of a bare service search ("dentist"); put the town in the keyword ("dentist columbus ohio"), or use maps_search_places for the Maps rank.

6 credits flat, also when the target is not in the top 100. NoData (free) only when the keyword has no organic results. Cached 24 hours.

"how strong is competitor.com", "how much traffic does X get", sizing a site before a deeper look.

• The keywords behind the traffic, use seo_get_ranked_keywords.
• Link counts, use seo_get_backlink_summary (its domain_rank equals this one).
• Many domains at once, use seo_get_domain_ratings for domain rank or seo_get_traffic_estimates for traffic.

One record with domain_rank (0 to 1000 on DataForSEO, the same kind of number as Ahrefs DR or Moz DA but not the same scale), organic_traffic, organic_keywords, organic_traffic_cost (USD), positions (top_3, top_10, top_100), keyword_changes (new, up, down, lost since the provider's previous update), paid_traffic, paid_keywords, top_pages[] (url, organic_traffic, organic_keywords), history[] (12 months: month, organic_traffic, organic_keywords) only with history true. null = provider has no data. A traffic figure saved before 1 November 2026 may be on DataForSEO's older traffic model: take a new baseline rather than compare across that date. history[] may keep the older model, so compare its months with each other, not with organic_traffic.

15 credits; +56 with history. Cached 7 days.

"what does competitor.com rank for", "which keywords send traffic to this page", building a list of a site's topics.

• Keywords a competitor has that you do not, use seo_get_keyword_gap.
• One keyword's position, use seo_get_position.
• New keyword ideas, use seo_search_keywords.

A list. Each row has keyword, rank, type (organic, featured_snippet or local_pack; ads excluded), previous_rank (null = did not rank at the provider's previous update), is_new, url, volume, kd, cpc, intent, traffic (estimated monthly visits from this keyword), serp_features[] (SERP feature types on the keyword's page). A keyword can appear once per type. Sorted by traffic, highest first. rank counts every element on the page, ads and features included, so a keyword in the organic top 100 can read rank 104. null = provider has no data. A traffic figure saved before 1 November 2026 may be on DataForSEO's older traffic model: take a new baseline rather than compare across that date.

5 + 5 per 100 rows. Default 100 rows = 10 credits. Cached 7 days.

"who competes with example.com in search", "which sites show up for the same queries as X", choosing competitors for a keyword gap.

• The keywords themselves, use seo_get_keyword_gap.
• A single domain's strength, use seo_get_domain_overview.

A list. Each row has domain, shared_keywords, avg_position, organic_traffic, organic_keywords, paid_traffic, paid_keywords. Sorted by shared keywords. The target itself is excluded. A traffic figure saved before 1 November 2026 may be on DataForSEO's older traffic model: take a new baseline rather than compare across that date.

5 + 5 per 100 rows. Default 100 rows = 10 credits. Cached 7 days.

"what does competitor.com rank for that we do not", "find gaps against X", content opportunities from a rival.

• Everything a domain ranks for, use seo_get_ranked_keywords.
• Finding who the competitors are, use seo_get_serp_competitors.
• Fresh ideas around a topic, use seo_search_keywords.

A list. Each row has keyword, competitor, competitor_rank, competitor_url, volume, kd, cpc, intent. Sorted by volume.

5 + 5 per 100 rows. Default 100 rows = 10 credits. Cached 7 days.

"how many links does X have", "what is X's link profile like", a quick authority check alongside seo_get_domain_overview.

• The individual links or their anchor text, use seo_get_backlinks.
• The sites linking, use seo_get_referring_domains.
• Domain rank for many domains, use seo_get_domain_ratings.

One record with domain_rank (equals seo_get_domain_overview's domain_rank), backlinks, referring_domains, referring_main_domains, referring_ips, dofollow_share (0 to 1), broken_backlinks (links to a page of the target that answers 4xx or 5xx), broken_pages (such pages), spam_score (backlinks' average, 0 to 100), target_spam_score, first_seen, and counts by link type, attribute, placement, platform, TLD and country (top 10). null = provider has no data.

10 credits flat. Cached 7 days.

"show me the links to this page", "which pages link to competitor.com", finding link sources to replicate, "which links did we lose" (status lost).

• Totals only, use seo_get_backlink_summary.
• One row per linking site, use seo_get_referring_domains.
• Rating the linking sites, use seo_get_domain_ratings.

A list. Each row has url_from, url_to, domain_from, dr_from, page_title, anchor, dofollow, rel[] (nofollow, sponsored, ugc and other rel values), type, spam_score (0 to 100), url_to_status (HTTP status of url_to), broken (url_to answers 4xx or 5xx), first_seen, last_seen (for a lost link, about when it went), lost (only with status lost or all). dr_from is the linking domain's own rank, 0 to 1000.

10 + 1.5 per 100 rows. Default 100 rows = 12 credits. Cached 7 days.

"who links to competitor.com", "build a list of sites to pitch for links", link prospecting from a rival's profile, "which sites stopped linking to us" (status lost).

• Every individual link, use seo_get_backlinks.
• Totals, use seo_get_backlink_summary.
• Rating your own list of domains, use seo_get_domain_ratings.

A list. Each row has domain, rank_passed (0 to 1000: the rank this domain's links pass to the target, not the domain's own rank, which seo_get_domain_ratings gives), backlinks, referring_pages, dofollow_backlinks, broken_backlinks (its links to a page of the target that answers 4xx or 5xx), spam_score, first_seen, lost (a link from it was lost; only with status lost or all). Sorted by rank_passed, so the strongest linking sites are not necessarily first: rate the domains before filtering by authority.

10 + 1.5 per 100 rows. Default 100 rows = 12 credits. Cached 7 days.

"rate these domains", "which of these sites are worth a link", filtering a prospect list by authority.

• Traffic numbers, use seo_get_traffic_estimates (10x the cost).
• A full profile of one domain, use seo_get_domain_overview or seo_get_backlink_summary.

A list. Each row has domain, domain_rank (0 to 1000 on DataForSEO, for the host as given; 0 for a domain the index does not know), ahrefs_dr (Ahrefs Domain Rating, 0 to 100, always for the registered domain, so www.github.com and gist.github.com both get github.com's; 0 for a domain Ahrefs does not know, null when it did not answer). One row per distinct domain, in the order first given: duplicates and case variants are merged, and a full URL is rated by its host. ahrefs_status says what a null ahrefs_dr means: ok (Ahrefs has no rating), partial (the domains in ahrefs_unanswered got no answer), failed or not_configured (Ahrefs did not answer; the null says nothing). ahrefs_attribution: wherever you show ahrefs_dr, show its text linked to its url next to it. errors[] lists inputs that were not valid domains.

7 + 2.5 per 100 domains, for domain_rank; ahrefs_dr adds nothing. Default 100 domains = 10 credits. Cached 7 days, or 1 hour when ahrefs_status is not ok.

"how much traffic do these sites get", comparing a list of domains by size, checking a prospect list for reach.

• Authority, use seo_get_domain_ratings (a tenth of the cost).
• One domain in depth, use seo_get_domain_overview.

A list. Each row has domain, organic_traffic, organic_keywords, paid_traffic. One row per input domain in the order given. null = provider has no data. A traffic figure saved before 1 November 2026 may be on DataForSEO's older traffic model: take a new baseline rather than compare across that date. errors[] lists inputs that were not valid domains.

50 + 50 per 100 domains. Default 100 domains = 100 credits. Cached 7 days.

"check the on-page SEO of this URL", "what schema does this page use", "what jobs are on their careers page", a quick look before a crawl.

• A whole site, use seo_run_technical_crawl.
• Rankings for the page, use seo_get_ranked_keywords with the URL.
• What the page ranks against, use seo_get_serp.

One record with url, final_url, status, title, meta_description, canonical, robots_meta, lang, h1[], h2[], word_count, schema_types[], links_internal, links_external, images, images_without_alt; with include, links[] (text, url) and text (without nav, header and footer). null = the tag is absent.

0 credits, rate limited. Cached 1 hour.

"audit example.com", "crawl the site for broken links and duplicate titles", a technical health check.

• One page, use seo_get_page.
• Rankings or traffic, use seo_get_domain_overview.
• Lighthouse scores, which it does not run.

A task_id at once, because the work runs in the background. When it is done, get_task returns target, pages_requested, pages_crawled, rendered, onpage_score, status_codes (crawled pages per HTTP status), broken_links (links, not pages: one broken link in a template counts once per page), broken_resources, non_indexable (URLs blocked from indexing by robots.txt, headers or meta tags, counting linked URLs robots.txt kept the crawler from, so it can exceed pages_crawled), duplicate_titles, duplicate_descriptions, issues[] (check, pages, sample_urls[]). Results expire after 30 days.

5 credits per 100 pages; 50 per 100 pages rendered. The charge is on max_pages requested, not pages crawled. Default 1,000 pages = 50 credits.