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gsc-mcp

Get Performance Overview

get_performance_overview

Retrieve a summary of clicks, impressions, CTR, and average position for a site over a specified date range. Use it to assess search performance quickly.

Instructions

Get a summary of clicks, impressions, CTR, and average position for a property.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
end_dateYesEnd date YYYY-MM-DD
site_urlYesProperty URL
start_dateYesStart date YYYY-MM-DD
search_typeNoOne of: web, image, video, news, discover, googleNewsweb

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.9/5.0
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool returns a 'summary,' implying aggregated data, but does not disclose whether this is a read-only operation, any permission requirements, rate limits, date range handling, or response shape beyond the output schema. For a tool with zero annotation coverage, 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?

The description is a single, front-loaded sentence with zero waste. It conveys the core purpose immediately and avoids any fluff. This is an example of efficient, concise writing.

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?

Although an output schema exists and covers return values, the description lacks context for an agent to properly choose this tool among many similar siblings. It does not explain what 'summary' means (e.g., whether it aggregates across the date range, whether it includes totals or averages), nor does it clarify the distinction from get_search_analytics. Given the tool's low complexity and full schema coverage, more contextual guidance would be expected.

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 (site_url, start_date, end_date, search_type) are already documented with descriptions and defaults. The description adds no extra meaning to parameters—it only mentions the output metrics. Baseline of 3 is appropriate since the schema already handles parameter semantics.

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 description clearly states the verb 'Get' and the resource: a summary of clicks, impressions, CTR, and average position for a property. It distinguishes itself from siblings like get_search_analytics by indicating a 'summary' rather than detailed analytics, though it does not explicitly name an alternative. The purpose is specific and unambiguous.

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?

The description provides no guidance on when to use this tool versus alternatives. It does not mention any conditions, exclusions, or suggest when a different sibling (e.g., get_search_analytics for detailed data, compare_periods for comparisons) would be more appropriate. An agent must infer usage from the name and schema alone.

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