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appscaptain

Google Search Console MCP Server

by appscaptain
OverviewSchemaRelated ServersScoreDiscussions
Python
Hybrid

get_advanced_search_analytics

Retrieve Google Search Console search analytics with custom dimensions, filters, sorting, and pagination to analyze SEO performance.

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

Tool Definition Quality

A4.4/5.0
Behavior4/5

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

No annotations provided, so the description carries the full burden. It discloses meaningful behavioral details: domain property coverage, filter override semantics, data freshness lag, and pagination. However, it doesn't explicitly state that the operation is read-only or mention access requirements, which would be even stronger.

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 leads with a concise summary sentence, then uses a well-organized Args list. Every line adds essential parameter information; no redundancy or filler. The length is justified by 14 parameters.

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?

All parameters are thoroughly explained with defaults, examples, and edge-case behavior (domain properties, filter override, data_state). With an output schema present, return value explanation isn't needed. The description fully equips an agent to select and invoke this tool.

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%, and the description compensates fully by defining every parameter with formats, defaults, valid values, and an example for 'filters'. Includes constraints like max row_limit and data_state options, going well 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?

Clearly states it retrieves advanced search analytics data with sorting, filtering, and pagination. The verb 'Get' and resource 'advanced search analytics data' are specific. Though it doesn't explicitly name a sibling tool, the 'advanced' qualifier and enumeration of capabilities distinguish it from simpler analytics 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?

Provides context on parameter usage (site_url from list_properties, filters override individual filter params, data_state options) but doesn't explicitly state when to use this tool vs. siblings like get_search_analytics. The usage guidance is implied rather than direct.

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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