Agent Data API

ai_keyword_demand

Idempotent

Modeled (estimated) AI-search demand for up to 10 keywords with 12-month history (DataForSEO AI Optimization Keyword Search Volume). Returns: JSON with estimate, source, methodology, keywords, not_found. PAID: 0.04 USDC per call (USDC on eip155:8453, x402 v2). Requires an x402-capable MCP client that attaches the payment in _meta["x402/payment"] (e.g. createx402MCPClient from @x402/mcp). Without a payment this tool returns a "payment required" result and charges nothing. NOTE: Modeled estimate, not a measured count. DataForSEO calculates AI search volume from statistical data on questions in Google's 'People Also Ask' results; it does not report actual prompt counts from any AI platform (ChatGPT, Gemini, Perplexity, ...). Use it as a relative demand indicator.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "keywords": "<keywords>"
    },
    "name": "ai_keyword_demand"
  }
}

Input Schema

Name	Required	Description
`keywords`	Yes	Keywords to look up: 1 to 10 entries, each up to 80 characters / 10 words. Lowercased, duplicates removed.
`language_code`	No	Language code such as en or de. Default: English if available for the country, else its first language. Unsupported country/language pairs are refused before payment.
`location_code`	No	DataForSEO location code. Country level: 2840 = United States (default), 2276 = Germany, 2040 = Austria, 2756 = Switzerland. Google SERP, Maps, News, Images and Local Market Check also accept city/region codes in Germany, Austria and Switzerland (free lookup: GET /api/v1/locations?q=...).

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedOct 23, 2026

changedInput schema / properties / location_code / description

Previous value: -"DataForSEO country code. 2840 = United States (default), 2276 = Germany, 2826 = United Kingdom. Country-level codes only."New value: +"DataForSEO location code. Country level: 2840 = United States (default), 2276 = Germany, 2040 = Austria, 2756 = Switzerland. Google SERP, Maps, News, Images and Local Market Check also accept city/region codes in Germany, Austria and Switzerland (free lookup: GET /api/v1/locations?q=...)."

First observedOct 22, 2026

TDQS

A4.1/5.0

Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Discloses cost (0.04 USDC on eip155:8453, x402 v2), required client capability, where the payment must be attached (_meta["x402/payment"]), and the failure mode with no payment ("payment required" result, nothing charged). It also discloses the return keys and the methodological limitation of the estimate. Consistent with readOnlyHint=false, openWorldHint=true, idempotentHint=true.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Core purpose and return shape are front-loaded, then payment mechanics, then the modeling caveat. It is long but nearly every sentence carries decision-relevant information. Slight redundancy between "Modeled (estimated)" and the closing NOTE paragraph.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

No output schema exists, and the description compensates by enumerating the return keys (estimate, source, methodology, keywords, not_found). Cost, auth/client prerequisite, failure behavior and interpretation limits are all covered, so an agent has everything needed to call and interpret it.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100% and all three parameters are documented there, including defaults, limits and location codes, so the description adds no parameter-level detail. It only reinforces the 10-keyword cap and 12-month window. Baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb+resource with scope: modeled AI-search demand for up to 10 keywords with 12-month history, plus the upstream source (DataForSEO AI Optimization Keyword Search Volume). It is clearly distinct from generic volume tools like keyword_metrics, but never names a sibling to route against.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

"Use it as a relative demand indicator" plus the explicit caveat that it is modeled, not measured, tells the agent the appropriate use. It lacks any when-not-use or alternative-tool routing (e.g. keyword_metrics for actual search volume).

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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