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shutovdef-dotcom

Google Search Console MCP Server

get_advanced_search_analytics

Get sorted and filtered Google Search Console search analytics data with pagination, supporting multiple dimensions and search types for in-depth SEO performance analysis.

Instructions

Get advanced search analytics data with sorting, filtering, and pagination.

Args:
    site_url: Exact GSC property URL from list_properties (e.g. "https://example.com/" or
              "sc-domain:example.com"). Domain properties cover all subdomains — use the
              domain property as site_url and filter by page to analyze a specific subdomain.
    start_date: Start date in YYYY-MM-DD format (defaults to 28 days ago)
    end_date: End date in YYYY-MM-DD format (defaults to today)
    dimensions: Dimensions to group by, comma-separated (e.g., "query,page,device")
    search_type: Type of search results (WEB, IMAGE, VIDEO, NEWS, DISCOVER)
    row_limit: Maximum number of rows to return (max 25000)
    start_row: Starting row for pagination
    sort_by: Metric to sort by (clicks, impressions, ctr, position)
    sort_direction: Sort direction (ascending or descending)
    filter_dimension: Single filter dimension (query, page, country, device). Use 'filters' instead for multiple filters.
    filter_operator: Single filter operator (contains, equals, notContains, notEquals)
    filter_expression: Single filter expression value
    filters: JSON array of filter objects for AND logic across multiple dimensions. Overrides
             filter_dimension/filter_operator/filter_expression when provided. Each object must
             have 'dimension', 'operator', and 'expression' keys. Valid dimensions: query, page,
             country, device. Valid operators: contains, equals, notContains, notEquals.
             Example: [{"dimension":"country","operator":"equals","expression":"usa"},
                       {"dimension":"device","operator":"equals","expression":"MOBILE"}]
    data_state: Data freshness — "all" (default, matches GSC dashboard) or "final" (confirmed data only, 2-3 day lag)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
filtersNo
sort_byNoclicks
end_dateNo
site_urlYes
row_limitNo
start_rowNo
data_stateNo
dimensionsNoquery
start_dateNo
search_typeNoWEB
sort_directionNodescending
filter_operatorNocontains
filter_dimensionNo
filter_expressionNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

With no annotations provided, the description carries full behavioral disclosure. It covers data freshness (data_state), pagination (start_row, row_limit), filter logic (single vs multiple filter parameters), and domain property nuances. It does not mention rate limits, error handling, or performance, but key behaviors are transparent.

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 a clear purpose sentence and organized into a readable Args block. While slightly verbose for some parameter descriptions, the structure is clear and each parameter has its own line. Could be tightened without losing clarity.

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?

Given the tool's complexity (14 parameters, pagination, multiple filter modes) and the presence of an output schema, the description covers most essential usage context: defaults, allowed values, parameter interactions. It lacks error case handling or performance notes, but overall it enables effective use.

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

Parameters5/5

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

Schema description coverage is 0%, so the description must compensate. It provides detailed explanations for all 14 parameters, including defaults, formats, allowed values, examples, and interactions (e.g., filters overrides filter_dimension/filter_operator/filter_expression). This adds significant meaning beyond the bare schema.

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 description clearly states 'Get advanced search analytics data with sorting, filtering, and pagination.' It uses a specific verb and resource, and the term 'advanced' distinguishes it from sibling tool 'get_search_analytics'.

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 detailed parameter guidance (e.g., site_url format, filter overrides, data_state options) but does not explicitly state when to use this tool versus alternatives like 'get_search_analytics' or other siblings. Usage is implied but not contrasted.

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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