dataforseo

DataForSEO

Agent-callable tools for the DataForSEO API v3 (https://api.dataforseo.com/v3/): search-engine, SEO, and AI-search data. Look up Google organic SERPs; research keywords (suggestions, related terms, search volume, difficulty, intent); analyze domains (ranking keywords, rank overview, organic-traffic estimates); inspect backlink profiles; search Google Maps business listings; run an on-page SEO audit; query AI models (ChatGPT, Claude, Gemini, Perplexity) and track how brands and domains are mentioned in AI-generated answers. All 33 tools are read-only data queries against DataForSEO's live (synchronous) endpoints.

Independent, unofficial connector for DataForSEO. Not affiliated with, endorsed by, or sponsored by DataForSEO. "DataForSEO" is a trademark of its owner, used only to identify the service this connector works with.

When to use this

• SERP & keyword research — see who ranks for a query, expand a seed keyword, or pull volume / CPC / difficulty / intent for a keyword list.
• Domain & competitor analysis — the keywords a domain ranks for, its rank overview, estimated organic traffic (current or historical), and its backlink profile (summary, individual links, referring domains, anchors).
• Local & on-page — find Google Maps businesses by category or location, or audit a single page's on-page SEO.
• AI-search visibility — ask an LLM a prompt, or track where a brand / domain / keyword is mentioned across AI answers (top pages, top domains, aggregate metrics).

Setup

This is an agentskills.io skill.

If the connector has not been installed as a skill yet, install it first with npx skills add zapier/connectors --skill dataforseo (or your harness's own skill-install mechanism), then continue here. Installing the skill copies these files, not dependencies. Before running the CLI, a local MCP server, or zapier-sdk auth commands, run npm install --omit=dev here once. Importing the published package as a dependency in your own project instead? That npm install already resolves everything — see references/use-as-sdk.md.

Want the actual repo source instead — to browse references/, run this connector's tests, or hack on it? See README.md for a scoped git clone.

The connector runs on Node.js 22.18+. Pick the reference that matches how you're running it, and load it before doing anything else:

You have...	Load
An MCP-aware client — tools may already be loaded (e.g. mcp__dataforseo__<tool>), or you can register a local server yourself (or guide the user to)	references/use-as-mcp.md
Terminal / subprocess access (you can run node)	references/use-as-cli.md
Only your own code, importing this package as a dependency	references/use-as-sdk.md
No tool access, no terminal, no ability to import this package — you write your own code that calls the DataForSEO API directly (e.g. a code-execution sandbox)	references/use-as-recipe.md

Scripts

All scripts use the single connection dataforseo. Many take a location_name / language_name pair (full names, e.g. "United States" / "English") — call listLocationsAndLanguages to resolve exact accepted values. List tools page with limit / offset.

Script	Script name	Connections	Description
scripts/getGoogleOrganicSerp.ts	getGoogleOrganicSerp	dataforseo	Fetch live parsed Google organic results for a keyword.
scripts/getKeywordSuggestions.ts	getKeywordSuggestions	dataforseo	Expand a seed keyword into long-tail queries that contain it.
scripts/getRelatedKeywords.ts	getRelatedKeywords	dataforseo	Get keywords from Google's "searches related to" block.
scripts/getKeywordOverview.ts	getKeywordOverview	dataforseo	Full metrics (volume, CPC, competition, difficulty, intent) for known keywords.
scripts/getKeywordDifficulty.ts	getKeywordDifficulty	dataforseo	Keyword Difficulty (0–100) for up to 1,000 keywords.
scripts/getSearchVolume.ts	getSearchVolume	dataforseo	Google Ads search volume, CPC, and competition for keywords.
scripts/getAiKeywordSearchVolume.ts	getAiKeywordSearchVolume	dataforseo	Estimated keyword usage volume inside AI tools.
scripts/getSearchIntent.ts	getSearchIntent	dataforseo	Classify the search intent of up to 1,000 keywords.
scripts/getRankedKeywords.ts	getRankedKeywords	dataforseo	List the keywords a domain or URL ranks for in Google.
scripts/getDomainRankOverview.ts	getDomainRankOverview	dataforseo	A domain's organic + paid search overview.
scripts/getOrganicTraffic.ts	getOrganicTraffic	dataforseo	Estimate current monthly organic traffic for up to 1,000 domains.
scripts/getHistoricalTraffic.ts	getHistoricalTraffic	dataforseo	Estimate monthly organic traffic over the past ~12 months.
scripts/getBacklinksSummary.ts	getBacklinksSummary	dataforseo	Overview of a single target's backlink profile (totals, rank, spam score).
scripts/getBacklinks.ts	getBacklinks	dataforseo	List individual backlinks to a target with anchors and attributes.
scripts/getBacklinksBulkPagesSummary.ts	getBacklinksBulkPagesSummary	dataforseo	Backlink counts for up to 1,000 pages/domains at once.
scripts/getReferringDomains.ts	getReferringDomains	dataforseo	Overview of the domains linking to a target.
scripts/getBacklinkAnchors.ts	getBacklinkAnchors	dataforseo	Anchor texts used in backlinks to a target.
scripts/searchBusinessListings.ts	searchBusinessListings	dataforseo	Search Google Maps business listings by category, name, or location.
scripts/getBusinessCategoriesAggregation.ts	getBusinessCategoriesAggregation	dataforseo	Count Google Maps businesses grouped by category.
scripts/auditPage.ts	auditPage	dataforseo	Run an instant on-page SEO audit of a single URL.
scripts/getChatGptResponse.ts	getChatGptResponse	dataforseo	Send a prompt to a ChatGPT model and get its response.
scripts/getChatGptSearchResults.ts	getChatGptSearchResults	dataforseo	The web results ChatGPT cited for a keyword search, as structured items.
scripts/getChatGptSearchResultsHtml.ts	getChatGptSearchResultsHtml	dataforseo	Raw HTML of ChatGPT's search results page for a keyword.
scripts/getClaudeResponse.ts	getClaudeResponse	dataforseo	Send a prompt to a Claude model and get its response.
scripts/getGeminiResponse.ts	getGeminiResponse	dataforseo	Send a prompt to a Gemini model and get its response.
scripts/getPerplexityResponse.ts	getPerplexityResponse	dataforseo	Send a prompt to a Perplexity model and get its response.
scripts/getLlmMentions.ts	getLlmMentions	dataforseo	Find where brands/domains/keywords are mentioned in AI answers.
scripts/getLlmMentionsTopPages.ts	getLlmMentionsTopPages	dataforseo	Rank pages most cited alongside your targets in AI answers.
scripts/getLlmMentionsTopDomains.ts	getLlmMentionsTopDomains	dataforseo	Rank domains most cited alongside your targets in AI answers.
scripts/getLlmMentionsAggregatedMetrics.ts	getLlmMentionsAggregatedMetrics	dataforseo	Aggregate AI-mention metrics (mention counts and AI search volume) for your targets.
scripts/getLlmMentionsCrossMetrics.ts	getLlmMentionsCrossMetrics	dataforseo	AI-mention metrics grouped by custom keys for comparison.
scripts/getAccountBalance.ts	getAccountBalance	dataforseo	Account credit balance, plan limits, and rate (also the auth check).
scripts/listLocationsAndLanguages.ts	listLocationsAndLanguages	dataforseo	List the exact location and language names DataForSEO accepts.

Disambiguation & refusals

This connector is read-only and live-only — it retrieves data, one query per call. It does not schedule or monitor tasks over time, run full-site crawls, or create/update/delete anything. If asked to do something outside that surface, say it's unsupported and stop — don't substitute another tool and report success for work you didn't do. Specifically:

• No task scheduling or ongoing monitoring. Each tool returns a one-shot live result; there is no "track rankings/backlinks over time" or background job. To trend a metric, the agent calls the tool again later and compares.
• No full-site crawl. auditPage audits a single URL only. There is no tool to crawl an entire site.
• No writes. Nothing here modifies a Google property, a website, or a DataForSEO resource; there is nothing to create, update, or delete.
• ChatGPT-platform LLM mentions are US/English only. getLlmMentions with platform: "chat_gpt" has no data outside the United States / English locale. If asked for another locale, say the data isn't available and stop — don't call getChatGptResponse (a live single-prompt chat, not mentions data) and present its output as mentions data, and don't silently swap to platform: "google" or a SERP search and report that instead without flagging the limitation.

Because every tool is a read that takes explicit query values (keywords, domains, URLs), there is no name-lookup-then-write step that needs disambiguation.

Auth

Every shape passes auth as one connection selector, not the secret — a [<resolver>:]<value> string. Every connector accepts zapier:<connection-id> (Zapier-managed auth — routes through Zapier's auth, retries, and governance layer); some also accept one or more direct-token resolvers (naming and count vary per connector) — check this connector's own resolvers rather than assuming. The <resolver>: prefix is optional; a bare value goes to the first resolver that claims it — a UUID-shaped bare value always claims zapier:. Each script declares the connections it needs and the resolvers each accepts. The exact syntax for passing a connection (and how to see this connector's resolver list) differs by shape — see the reference you loaded above.

Checking what's already configured first? Don't dump environment values to do it — env or env | grep <name> prints the value along with the name, leaking a live credential into the transcript if one is set. Check names only (env | cut -d= -f1 | grep -i <name>) or test a known name directly ([ -n "$VAR_NAME" ]).

No connection yet? Pick one — and follow the reference's own flow to obtain it; never just ask the user for a connection id or token as if they already have one memorized:

	Load
Pass the credential directly	references/use-without-zapier.md
Route it through a Zapier connection	references/use-with-zapier.md

Output format

Every script returns a { data, meta } envelope:

• data — the script's result (the shape its outputSchema declares; see the reference you loaded above for how to inspect a script's exact schema in your shape).
• meta.outputDataValidation — what validating data did:
  • { skipped: false, droppedPaths: null } — validated, nothing removed.
  • { skipped: false, droppedPaths: [...], instruction } — validated, but those paths were stripped from data: fields the script returned from the API that the outputSchema doesn't declare. If you need them, re-run with output validation skipped.
  • { skipped: true } — validation was bypassed; data is the raw, unchecked script output.

Reading dropped fields / skipOutputDataValidation. To receive the raw, unvalidated result, opt out of output validation (the exact syntax differs by shape — see the reference you loaded above). Input validation is never skipped.

Trimming the result / filterOutputData. To shrink a large result down to the fields you need, pass a jq expression that post-processes data (again, exact syntax per shape). The jq runs against data only, NOT the { data, meta } envelope, so write it rooted at data (run the script's --help — or your shape's equivalent — to see its output schema). The transformed value replaces data, meta is preserved, and the result is NOT re-validated against the output schema.

References

Load the matching reference file before working in that area:

Reference	Covers	Load it when
references/dataforseo-api-gotchas.md	In-body error status codes over HTTP 200, the array-of-tasks request format, the response envelope, auth, rate limits, exact location/language names, the filters array-expression syntax, limit/input caps, and metric-specific notes (backlink rank, keyword difficulty, related-keyword depth, SERP depth, LLM-mentions platform, Perplexity web search).	Any call fails with data-looking-empty results, you're building a filters expression, hitting a limit, resolving a location/language, or interpreting a metric's range.
references/use-as-recipe.md	A reference implementation of the request/response shape for each endpoint — the array-wrapped POST body, the two-level status check, and the per-tool endpoint/param table — with critical rules pointed at the gotchas.	Loaded by a harness writing its own code against the DataForSEO API (can't load the tools, run the CLI, or import the package).