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rankparse-mcp

by io.github.abhibavishi

get_google_ads_keyword_ideas

Read-onlyIdempotent

Discover NEW keyword ideas from seed terms and/or a URL, with average monthly search volume, competition level, and top-of-page bid ranges. Use this for keyword research and content planning: "what should I target?". Supply seed keywords, a URL, or both. Requires Google Ads to be connected and an Ads account selected. Direct the user to rankparse.com/dashboard/integrations. Returns search volume and competition data, NOT keyword rankings; use the Google Search Console tools for ranking and position data.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlNoA page or site URL to derive keyword ideas from, e.g. "https://example.com/pricing"
limitNoMax ideas to return (default Google decides, max 1000)
keywordsNoSeed keywords to expand from, e.g. ["seo tools", "backlink checker"]. Max 20; provide these and/or url.
languageNoLanguage resource name, default "languageConstants/1000" (English)
geo_target_constantsNoLocation resource names, default ["geoTargetConstants/2840"] (United States). Max 10.
keyword_plan_networkNoSearch network to estimate against (default GOOGLE_SEARCH)
include_adult_keywordsNoInclude adult keywords in results (default false)

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint and destructiveHint false, so the safety profile is known. The description adds useful context about account prerequisites and clarifies the tool returns search volume/competition data, not rankings. No contradiction with annotations.

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 front-loaded with purpose and uses six sentences, each adding distinct value: purpose, use case, input, prerequisites, instructions, and clarification. No redundant or promotional language.

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?

The description covers inputs, prerequisites, return data, and exclusions. With no output schema, it explains what data is returned (search volume, competition, bid ranges). It does not discuss pagination or rate limits, but the schema's limit parameter mitigates this gap.

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?

The input schema covers all 7 parameters with detailed descriptions (100% coverage). The description adds minimal parameter-level info beyond saying to supply keywords and/or URL, which is already in the schema. Baseline 3 is appropriate.

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's function: 'Discover NEW keyword ideas from seed terms and/or a URL' with specific data outputs. It distinguishes from siblings by noting it returns search volume/competition, not rankings, and directs users to GSC tools for ranking data.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly says 'Use this for keyword research and content planning' and gives an example question. It also states prerequisites (Google Ads connected, Ads account selected) and provides a clear when-not-to-use: 'NOT keyword rankings; use Google Search Console tools.'

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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TDQS

A3.5/5.0
Disambiguation4/5

The tool set is largely well-disambiguated with clear prefixes (get_, outreach_, zeekeo_) and detailed descriptions for each tool. Some tools like get_site_explorer and get_site_health could be confused at a glance, but their descriptions clearly separate their purposes. Overall, the naming and descriptions prevent meaningful ambiguity.

Naming Consistency5/5

All tools follow a consistent get_ prefix for data retrieval, with sub-prefixes like get_gsc_, get_page_, and outreach_/zeekeo_ for distinct workflows. There is no mixing of naming conventions (e.g., camelCase) or inconsistent verb usage. The naming pattern is uniform and predictable.

Tool Count1/5

With 63 tools, this server vastly exceeds the typical 3-15 tool scope, categorizing as an extreme overflow. Even for a comprehensive SEO and outreach suite, the sheer number is overwhelming and likely includes redundant or overlapping functionality. This would be confusing for agents and users alike.

Completeness4/5

The tool set covers a wide range of SEO, backlink analysis, Google Search Console data, and outreach workflows, appearing nearly complete for its stated purpose. However, several tools are marked as 'v1 stub' (e.g., get_internal_links, get_schema_markup), indicating incomplete functionality. Despite these gaps, the overall coverage is extensive and well-rounded.

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