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jafforgehq

SEO Analytics MCP

by jafforgehq

gsc_search_analytics_raw

Execute raw Google Search Console queries to analyze search performance data with customizable parameters for comprehensive SEO insights.

Instructions

Run a raw Search Console Search Analytics query with full options.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
site_urlNo
start_dateNo
end_dateNo
dimensionsNo
row_limitNo
start_rowNo
search_typeNoweb
data_stateNo
aggregation_typeNo
dimension_filter_groupsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior2/5

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

With no annotations provided, the description carries full burden for behavioral disclosure but offers minimal information. It mentions 'raw' and 'full options' but doesn't describe authentication needs, rate limits, data freshness, error handling, or what 'raw' entails operationally. This is inadequate for a tool with 10 parameters and complex functionality.

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, efficient sentence that front-loads the core purpose. Every word earns its place, with no wasted verbiage or redundancy, making it easy to parse quickly.

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 (10 parameters, no schema descriptions, no annotations) and the presence of an output schema, the description is incomplete. It doesn't provide enough context for the agent to understand when to use it, what the parameters do, or behavioral aspects, despite the output schema handling return values. This leaves significant gaps for effective tool selection and invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate but fails to do so. It mentions 'full options' but doesn't explain any of the 10 parameters' purposes, relationships, or constraints (e.g., what 'dimensions' or 'aggregation_type' mean, date format requirements). The agent must rely solely on schema titles, which are minimal.

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 action ('Run') and resource ('Search Console Search Analytics query'), specifying it's a 'raw' query with 'full options'. However, it doesn't differentiate from sibling tools like 'gsc_top_pages' or 'gsc_top_queries', which likely provide more curated or specific data subsets rather than raw queries.

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 mentions 'full options' but doesn't explain what scenarios require this versus simpler sibling tools like 'gsc_top_pages' or 'gsc_query_page_pairs', leaving the agent to guess based on tool names alone.

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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