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cfp-seo-agent

cfp-seo-agent

by CFP-102
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Remote

google_trends

Idempotent

Compare up to five keywords' Google search interest over the past 12 months on a relative 0–100 scale to reveal trends and seasonal patterns.

Instructions

Google Trends interest over time (past 12 months, relative 0-100) for up to 5 keywords compared against each other (DataForSEO Google Trends Explore Live). Returns: JSON with keywords, points. SANDBOX (development): returns dummy data, no payment.

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": "google_trends"
  }
}

Input Schema

NameRequiredDescriptionDefault
keywordsYesKeywords to look up: 1 to 5 entries, each up to 80 characters / 10 words. Lowercased, duplicates removed.
language_codeNoLanguage 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_codeNoDataForSEO 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.

  1. First observedv0.1.0

TDQS

A3.9/5.0
Behavior4/5

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

With annotations covering safety, the description still adds real context: a live paid backend plus a SANDBOX mode that returns dummy data with no payment, which is exactly the kind of caveat an agent needs. It stops short of stating cost, rate limits, or whether data is cached/refreshed.

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?

Three compact clauses: purpose and scope first, return shape second, sandbox caveat last. Every element carries information; the only minor cost is the dense parenthetical about the provider.

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

Completeness4/5

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

For a three-parameter, no-output-schema tool, the description covers purpose, output fields (keywords, points), 12-month window, relative scale, and the sandbox behavior. What's missing is production cost/payment expectation and any note on how often data refreshes.

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 coverage is 100%, so keywords, language_code, and location_code are already well documented. The description only echoes the 5-keyword cap and adds the 0-100 relative scale, which is output semantics rather than parameter guidance, so baseline 3 applies.

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

Purpose5/5

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

The definition names a specific resource (Google Trends interest over time) and specifies the scope: past 12 months, relative 0-100, up to 5 keywords compared against each other. It also names the underlying endpoint (DataForSEO Google Trends Explore Live), which makes it easy to tell apart from siblings such as keyword_metrics or regional_data.

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?

The description provides enough context to infer the use case (comparative keyword interest over the last year, max 5 terms), but never says when to prefer this over alternatives like keyword_metrics, ai_keyword_demand, or regional_data, and gives no explicit exclusions.

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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