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Domain position in Google

domain_position
Read-only

Check where a domain ranks in Google organic results for a keyword by country and device.

Instructions

Find where a domain ranks in Google's organic results for a keyword, in a country and on a device, right now. Prefer it over google_search when only one site matters: it returns that site's best position and every other position, or a note that the site is outside the checked depth. A subdomain counts as the domain: example.com also matches blog.example.com. Billed like google_search, per page of 10 results of depth that received results (https://serper.live/pricing).

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": {
      "domain": "<domain>",
      "query": "<query>",
      "country": "<country>"
    },
    "name": "domain_position"
  }
}

Input Schema

NameRequiredDescriptionDefault
depthNoHow many organic results to check, 1–100. Default: 10. Use 30 or more to see positions beyond the first page.
queryYesSearch keyword, exactly as a person would type it into Google.
deviceNoBrowser persona Google sees. Desktop and mobile rankings often differ. Default: desktop.
domainYesDomain to look for, e.g. "example.com". Scheme, path and a leading www are ignored.
countryYesTwo-letter code of the market to search in, e.g. "US", "GB", "DE", "FR", "TR": Google sees a visitor from this country. Call list_countries for the markets that are open right now.
languageNoGoogle interface language (hl), e.g. "en", "de", "fr", "uk". Defaults to the language of the country; the market itself is set by country.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed3 schema fields changedv2.0.1
    • changedInput schema / $schema
      Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"
    • changedInput schema / properties / country / description
      Previous value: -"Two-letter code of the market to search in, e.g. \"US\", \"GB\", \"DE\", \"TR\". Call list_countries for the markets that are open right now."New value: +"Two-letter code of the market to search in, e.g. \"US\", \"GB\", \"DE\", \"FR\", \"TR\": Google sees a visitor from this country. Call list_countries for the markets that are open right now."
    • changedInput schema / properties / language / description
      Previous value: -"Google interface language (hl), e.g. \"en\", \"de\", \"uk\". Defaults to the language of the country."New value: +"Google interface language (hl), e.g. \"en\", \"de\", \"fr\", \"uk\". Defaults to the language of the country; the market itself is set by country."
  2. First observedv0.1.0

TDQS

A4.8/5.0
Behavior5/5

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

Goes well beyond the readOnly/openWorld/idempotent annotations: it discloses the subdomain matching rule, that results are a live snapshot ('right now'), that a below-depth note is returned instead of silence, and the billing model (per page of 10 results at the depth that actually returned results). Cost and edge-case semantics are exactly the kind of context annotations cannot carry.

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?

Four sentences, all load-bearing, with the core purpose front-loaded before alternatives and caveats. The final pricing sentence is slightly run-on ('per page of 10 results of depth that received results'), which costs a point but not comprehension.

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?

With six parameters, no output schema, and an open-world read, the description supplies everything an agent needs: what it returns (best position plus other positions), the no-match case, matching rules, and cost. Nothing essential is left to inference.

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

Parameters4/5

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

Schema coverage is 100%, so the baseline is 3, but the description adds real semantics the schema lacks: subdomain matching ('example.com also matches blog.example.com') disambiguates the domain parameter, and the depth/billing interaction clarifies what changing depth costs.

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 first sentence states a specific verb+resource+scope: rank lookup for a domain in Google organic results, parameterized by keyword, country, and device, at a point in time. It also names the sibling (google_search) it is not, so an agent can route between them without opening either schema.

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

Usage Guidelines5/5

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

Explicit selection rule: 'Prefer it over google_search when only one site matters.' The description also covers the degenerate case ('or a note that the site is outside the checked depth'), so the agent knows behavior when no match is found rather than inferring an empty result.

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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