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kevinmaqueda

MCP DataForSEO Server

by kevinmaqueda

check_serp_position

Check your domain's current Google ranking for any keyword. Retrieve exact position, URL, title, and SERP features for that search.

Instructions

Check the current Google ranking position for a domain on a specific keyword. Returns position, URL, title, and SERP features.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
depthNoNumber of results to check (default 100)
domainYesThe domain to find in search results (e.g., 'espacioneon.com')
keywordYesThe search keyword to check
country_codeNoCountry code. Available: ES, MX, AR, CO, US, GB, DE, FR, IT, PT, NL, BE, AT, CH, IE, PL, CZ, SE, DK, NO, FI, GR, HU, RO, BG, HR, SK, SI, LT, LV, EE, BR, CL, PEES
Behavior3/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It does disclose that the tool returns position, URL, title, and SERP features, which is useful. However, it does not mention limitations (e.g., rate limits, localization behavior), authentication needs, or behavior when the domain/keyword is not found. The lack of these details makes it only partially transparent.

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

Conciseness5/5

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

The description is a single, front-loaded sentence that states the purpose and then the return value. Every word contributes meaning, with no redundancy or filler. This is an exemplary model of conciseness.

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

Completeness3/5

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

Given the tool's moderate complexity (four parameters, no output schema, no annotations), the description is adequate but not thorough. It explains the core function and return fields, but lacks contextual details such as edge-case behavior, country-specific implications, or how this tool compares to sibling rank tools. The schema fills some gaps, but the description itself could be more complete.

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?

The input schema provides descriptions for all four parameters (100% coverage), so the baseline is 3. The tool's description adds no extra parameter semantics beyond mapping 'domain' and 'keyword' from the prose; it does not elaborate on depth or country_code, but the schema already covers them. Therefore, the description adds minimal value over the schema.

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 clearly identifies the tool's purpose: checking the current Google ranking position for a domain and keyword. It specifies the verb 'Check' and the resource 'Google ranking position,' and lists the returned data (position, URL, title, SERP features), which helps distinguish it from related tools like get_domain_rank. However, it does not explicitly name alternatives, so it misses the top score for differentiation.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives. It does not mention any context, prerequisites, exclusions, or comparative scenarios. This leaves the agent to infer usage from the name and schema alone, which is insufficient for a tool with many siblings.

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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