Agent Data API

keyword_difficulty

Idempotent

Keyword difficulty score (0-100) for up to 100 keywords (DataForSEO Labs Bulk Keyword Difficulty). Returns: JSON with 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.

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": "keyword_difficulty"
  }
}

Input Schema

Name	Required	Description
`keywords`	Yes	Keywords to look up: 1 to 100 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=...)."

AddedOct 22, 2026

TDQS

A4/5.0

Behavior5/5

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

Goes well beyond the annotations: it discloses a concrete price (0.04 USDC on eip155:8453, x402 v2), the exact payment attachment mechanism (_meta["x402/payment"]), a concrete client example (createx402MCPClient), and the no-payment fallback behavior (returns 'payment required', charges nothing). This is precisely the operational context an agent needs before invoking a paid tool, and nothing contradicts the annotations.

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?

The description is front-loaded with the core purpose and the return shape, then the payment requirements. The payment sentence is long but every clause (price, chain, protocol, header key, fallback) earns its place for a paid tool. Minor verbosity keeps it from a 5.

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?

Although there is no output schema, the description closes that gap by naming the return fields (keywords, not_found). Combined with the 100% schema coverage, the payment mechanics, and the precondition on the client, an agent has everything needed to call this correctly or know it cannot.

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%, so parameters are already documented well, and the description only restates the 1-100 keyword bound. It adds no syntax, formatting, or normalization detail (e.g., lowercasing, dedupe) beyond what the schema already carries, so this sits at the baseline.

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?

The description gives a specific verb-and-resource pairing: a 0-100 difficulty score for up to 100 keywords, sourced from DataForSEO Labs Bulk Keyword Difficulty. It is clearly distinct from siblings like keyword_metrics or keyword_ideas by naming the exact metric and its 0-100 scale. It stops short of explicitly directing the agent away from those sibling tools.

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

Usage Guidelines3/5

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

Usage context is implied rather than stated: it names the upstream data source and says the tool is PAID with an x402 prerequisite, which tells an agent when it is callable. However, it never says when to prefer this over keyword_metrics, keyword_ideas, or other keyword siblings, and no exclusion guidance is offered.

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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