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harisnadeem

searchconsole-mcp

by harisnadeem

query_search_analytics

Retrieve search analytics data including clicks, impressions, CTR, and position for a website. Filter by date range, dimensions, search type, and apply dimension filters to analyze performance.

Instructions

Query Search Analytics data for a website.

Args: site_url: The site to query, e.g. 'https://example.com/' or 'sc-domain:example.com'. start_date: Start date in YYYY-MM-DD format. end_date: End date in YYYY-MM-DD format. dimensions: Group results by these dimensions. Valid values: date, query, page, country, device, searchAppearance. Omit to get aggregate totals with no grouping. search_type: Type of search to filter by. Values: web (default), image, video, news, discover, googleNews. row_limit: Maximum number of rows to return (default 1000). start_row: Zero-based offset for pagination (default 0). data_state: Include only 'final' (default) confirmed data, or 'all'. aggregation_type: How to aggregate data. 'auto' (default), 'byPage', or 'byProperty'. dimension_filter_groups: List of filter groups to apply. Each group has 'groupType' ('and'/'or') and 'filters' list. Each filter: {dimension, expression, operator}. Operators: equals, notEquals, contains, notContains, beginsWith, notBeginsWith, endsWith, notEndsWith, isEmpty, isNotEmpty.

Returns: Dictionary with 'rows' (list of result rows) and 'responseAggregationType'. Each row contains dimension values in 'keys' plus: - clicks (total clicks) - impressions (total impressions) - ctr (click-through rate) - position (average search position)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
site_urlYes
start_dateYes
end_dateYes
dimensionsNo
search_typeNoweb
row_limitNo
start_rowNo
data_stateNofinal
aggregation_typeNo
dimension_filter_groupsNo
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It describes the return format and parameters but does not mention side effects, authentication, rate limits, or data freshness. As a query, it is assumed read-only, but this is not explicit.

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 well-structured with Args and Returns sections. It is slightly verbose but every sentence adds value. Minor redundancy (e.g., 'default' repeated) but overall efficient.

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 (10 parameters, no output schema, no annotations), the description covers all parameter semantics and return structure. However, it lacks error handling, rate limit info, or clarification on required permissions, which would be helpful.

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?

The schema has 0% description coverage, yet the description provides comprehensive details for each parameter: valid values, defaults, constraints, and examples. This adds substantial meaning beyond the raw 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 name 'query_search_analytics' combined with the opening sentence 'Query Search Analytics data for a website' clearly states the tool's function. It is distinct from sibling tools (sitemap and inspection tools), so there is no ambiguity.

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

Usage Guidelines4/5

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

The description provides detailed parameter documentation but does not explicitly state when to use this tool over alternatives. However, since siblings are unrelated, the context implies it is the primary analytics query tool, and the parameter descriptions give implicit guidance.

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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