gsc-mcp

Get Search Analytics

get_search_analytics

Retrieve Google Search Console search analytics by property and date range, with optional dimensions and filters to analyze queries, pages, countries, and devices.

Instructions

Query GSC search analytics data.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`filters`	No	List of filter dicts: [{"dimension": "query", "operator": "contains", "expression": "keyword"}]
`end_date`	Yes	End date in YYYY-MM-DD format
`site_url`	Yes	Property URL (e.g. 'https://example.com/' or 'sc-domain:example.com')
`row_limit`	No	Max rows to return. Max 5000 (default: 1000)
`start_row`	No	Pagination offset (default: 0)
`data_state`	No	'all' (includes partial data) or 'final' (2-3 day lag, more stable)	all
`dimensions`	No	List of dimensions. Options: query, page, country, device, searchAppearance, date
`start_date`	Yes	Start date in YYYY-MM-DD format
`search_type`	No	One of: web, image, video, news, discover, googleNews (default: web)	web

Output Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Sep 21, 2026

TDQS

C2.4/5.0

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 only says 'Query GSC search analytics data' and does not mention pagination behavior, data freshness (data_state), search type, or any rate limits. The schema documents parameters, but the description adds no behavioral context beyond the name.

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

Conciseness2/5

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

The description is only one sentence, which is concise, but it is under-specified. It adds almost no value beyond the tool name and title, failing to earn its place. For a tool with 9 parameters and many siblings, this brevity is not appropriately sized; it omits critical context.

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

Completeness2/5

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

Given the tool's complexity (9 parameters, rich schema, many sibling tools, and an output schema), the description is grossly incomplete. It does not explain what data is returned, how to interpret results, or when to choose this over alternatives. The schema provides parameter details, but the description itself offers no high-level context, leaving an agent without sufficient guidance for correct invocation.

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%, and each parameter has a meaningful description (e.g., site_url, dimensions, row_limit, data_state). The tool description itself adds no parameter-level information, but the schema fully covers semantics, so a baseline of 3 is appropriate per the rubric.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a clear verb and resource ('Query GSC search analytics data'), but it is vague about what specific analytics are returned and how it differs from sibling tools like get_performance_overview or compare_periods. It is not a tautology, but it lacks the specificity needed to distinguish among the many analytics-related tools.

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?

No guidance is provided on when to use this tool versus alternatives. The description gives no context on use cases, exclusions, or how it compares to batch_search_analytics, get_performance_overview, or compare_periods. An agent would have to infer usage from the name alone.

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