GSC MCP Core

gsc_opportunity_radar

Scans Google Search Console data to find high-impression, low-CTR SEO opportunity keywords. Uses a segmented CTR model to estimate incremental clicks after ranking improvement, and provides 3 prescription-grade recommendations (Title Optimization, AI Answer Capsule, Internal Linking). Output includes scan overview, top opportunities list, incremental gain forecast, and prioritization advice.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "siteUrl": "<siteUrl>"
    },
    "name": "gsc_opportunity_radar"
  }
}

Input Schema

Name	Required	Description
`topN`	No	Return Top N opportunities (default 10)
`siteUrl`	Yes	GSC site URL, e.g. https://example.com/
`daysBack`	No	Lookback window in days (default 7)
`maxPosition`	No	Maximum average position to include (default 20)
`minImpressions`	No	Minimum impressions filter (filters low-volume noise, default 100)

Schema Changelog

Changes observed during successful MCP inspections.

First observedNov 8, 2026

TDQS

A3.8/5.0

Behavior4/5

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

With no annotations, the description carries the behavioral burden and does well by disclosing the segmented CTR model, incremental-click estimation, three recommendation types, and output components. It still omits access prerequisites, read-only nature, data freshness, and rate limits.

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 two tight sentences: purpose is front-loaded, followed by method and output summary. Every sentence contributes useful information with no filler.

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?

For a five-parameter analytics tool with no output schema and no annotations, the description explains the computation approach, recommendation types, and return components. It is nearly complete, missing only access prerequisites and edge-case behavior.

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 five parameters. The description does not add parameter-specific meaning beyond referencing high-impression and low-CTR filtering, so baseline 3 applies.

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 states a specific verb ('Scans'), resource ('Google Search Console data'), target ('high-impression, low-CTR SEO opportunity keywords'), and expected outputs. It is clear what the tool does, though it does not explicitly contrast itself with the sibling gsc_inspect_url.

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 intended use is implied: finding and prioritizing SEO opportunities from GSC data. However, there is no explicit when-to-use, when-not-to-use, or alternative-routing guidance, such as when to use gsc_inspect_url instead.

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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