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jlnkrth

gsc-mcp-server

by jlnkrth

gsc_search_analytics

Query Google Search Console search analytics to retrieve clicks, impressions, CTR, and position, filterable by query, page, country, device, date, and search appearance.

Instructions

Query Google Search Console search analytics. Returns clicks, impressions, CTR, and position. Dimensions: query, page, country, device, date, searchAppearance.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeNoSearch type: 'web' (default), 'image', 'video', 'news', 'discover', 'googleNews'
end_dateYesEnd date (YYYY-MM-DD)
site_urlYesSite URL as registered in GSC (e.g. 'https://example.com/' or 'sc-domain:example.com')
row_limitNoMax rows (default 100, max 25000)
start_rowNoStarting row for pagination (default 0)
dimensionsNoDimensions to group by: 'query', 'page', 'country', 'device', 'date', 'searchAppearance'
start_dateYesStart date (YYYY-MM-DD)
page_filterNoFilter pages whose URL contains this string
query_filterNoFilter search queries containing this string (case-insensitive)
dimension_filtersNoOptional filters, e.g. [{"dimension":"query","operator":"contains","expression":"keyword"}]
Behavior2/5

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

With no annotations, the description carries full transparency responsibility. It does not state whether the operation is read-only, what permissions are required, how pagination works, or what the response structure looks like. It only mentions output metrics and dimensions, adding minimal behavioral context beyond the schema.

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 is very short and efficient, with three sentences covering the main action, the return values, and the dimensions. Each sentence adds essential information without redundancy or filler, and the main verb is front-loaded.

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?

The tool has 10 parameters, no output schema, and no annotations, yet the description is only a few sentences. It omits guidance on required parameters, pagination behavior, filtering capabilities, and response structure. The schema covers parameter semantics, but the description fails to provide the broader context needed for effective tool use.

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 all parameters are individually documented. The description restates the dimension list but adds no extra meaning about parameter usage, formats, defaults, or interactions beyond what the schema already provides.

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 the tool queries Google Search Console search analytics and lists the returned metrics (clicks, impressions, CTR, position) and available dimensions. This distinguishes it from sibling tools like gsc_list_sites and gsc_inspect_url, which handle site lists and URL inspection rather than analytics data.

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 implies use for search analytics queries but does not explicitly state when to use it versus alternatives or provide exclusions. It does not reference any sibling tools or offer guidance on when this tool is preferred, so usage context is only implied.

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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