Google Search Console MCP Server

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Query Search Analytics

query_search_analytics

Run a raw Search Analytics query with full control over dimensions, filters, and dates to get custom search performance data from Search Console.

Instructions

Run a raw Search Analytics query with full control over the request.

This is the unmodified API method. For the common cases prefer top_queries, top_pages, performance_by_date, performance_by_country, performance_by_device, compare_periods or query_all_rows.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`end_date`	Yes	Inclusive end date, YYYY-MM-DD (PST).
`site_url`	Yes	Property identifier.
`row_limit`	No	1 to 25,000. Page with start_row beyond that.
`start_row`	No	Zero-based index of the first row to return.
`data_state`	No	FINAL for finalised data only (default), ALL to include fresh partial data from the last ~2 days, HOURLY_ALL for hourly.
`dimensions`	No	Dimensions to group by, in order. Results are keyed by the combination of these, in the order supplied.
`start_date`	Yes	Inclusive start date, YYYY-MM-DD (PST).
`search_type`	No	WEB, IMAGE, VIDEO, NEWS, DISCOVER or GOOGLE_NEWS.	WEB
`aggregation_type`	No	AUTO, BY_PROPERTY or BY_PAGE. Use AUTO when grouping or filtering by PAGE.
`dimension_filter_groups`	No	Native filter groups, e.g. [{"groupType": "AND", "filters": [{"dimension": "QUERY", "operator": "CONTAINS", "expression": "buy"}]}]

Output Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Sep 14, 2026

TDQS

A3.7/5.0

Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It hints the query is 'raw' and 'full control', but says nothing about authorization requirements, rate limits, whether results are paginated (though the schema mentions paging), or what the return structure is (output schema exists, so that's partially covered). For a complex 10-parameter analytics tool with no annotations, this is a significant gap.

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?

Ten words in the first sentence and a single list of alternatives in the second — no filler, and the key distinction (raw vs. preset) is front-loaded.

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 10 parameters and no annotations, the description does not provide enough operational context (e.g., auth scope, rate limits, pagination behavior beyond what the schema implies). An output schema exists so return-value explanation is not required, but behavioral gaps remain for a complex query tool.

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?

Schema description coverage is 100%, so the schema already documents all 10 parameters depthfully. The description adds no parameter-level meaning beyond the schema. Baseline 3 is appropriate when the schema is comprehensive.

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 first sentence states a specific verb and resource ('Run a raw Search Analytics query') and the second sentence clarifies the tool's positioning ('unmodified API method'). However, it doesn't explicitly state what distinguishes it from the named siblings beyond being raw/not preset; the mechanism of distinction is implied by the alternative names.

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?

Explicitly names seven alternative tools for common cases (top_queries, top_pages, performance_by_date, etc.) and states the condition for using this tool ('full control over the request'), creating a clear when-to-use / when-to-use-something-else split.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.