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sonar

by app.trysonar
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Keyword Research

sonar_keyword_search
Read-onlyIdempotent

Research a keyword and related terms. Returns up to 10 rows — the seed keyword plus the store's top autocomplete suggestions — each with difficulty (0-100), popularity score, and results count. Use this to find keywords worth targeting; for metrics on terms you already know, sonar_keyword_metrics is cheaper. On prepaid API credits it costs 10 credits per call (rows that could not be computed are refunded); it needs a Sonar API key or connected account and is not part of the free tier. Answers within about 30 seconds. Each row carries measured_at (difficulty) and popularity_measured_at (popularity, can be older), ISO 8601 UTC; stale: true means at least one of them is older than 7 days. A related term that couldn't be computed in time is re-checked while the call's time budget allows (through the metrics endpoint, 1 credit per keyword served); one still not ready comes back marked pending (queued, not charged) — get it later with sonar_keyword_metrics. popularity (5-100) is the value Sonar's dashboard shows: Apple's Search Popularity when Apple has a real reading; when Apple reports a keyword below its threshold (popularity_apple 5, about 20) it is Sonar's estimate (at most 18). popularity_source says which (apple | proxy), popularity_apple is Apple's own reading (null on Android), popularity_proxy is Sonar's estimate beside a floored reading.

Input Schema

NameRequiredDescriptionDefault
queryYesSeed keyword to research (e.g. "meditation", "recipe app").
storeYesApp store. "ios" for Apple App Store, "android" for Google Play.
countryNoOne of Sonar's 72 keyword-research markets, as an ISO 3166-1 alpha-2 code (e.g. "us", "gb", "de", "jp", "br"). Keyword data isn't available for other storefronts. Default "us".us

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / properties / country / description
      Previous value: -"ISO 3166-1 alpha-2 country code (e.g. \"us\", \"gb\", \"de\"). Default \"us\"."New value: +"One of Sonar's 72 keyword-research markets, as an ISO 3166-1 alpha-2 code (e.g. \"us\", \"gb\", \"de\", \"jp\", \"br\"). Keyword data isn't available for other storefronts. Default \"us\"."
  2. First observed

TDQS

A4.6/5.0
Behavior5/5

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

Beyond the annotations, the description discloses paid-credit cost, refund behavior, API key/connected-account requirements, free-tier exclusion, and expected latency. It also explains stale/pending row semantics, measurement timestamps, and popularity source quirks, which are meaningful behavioral details not covered by annotations or schema.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with purpose and return shape, then moves through usage, cost/auth, timing, and field semantics. It is long but mostly earns its length; the popularity explanation is dense though still relevant for interpreting returned values.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema, the description carries return-value burden well: row count, fields, timestamps, stale/pending states, and popularity source are all explained. Combined with full parameter schema coverage and existing annotations, an agent has enough context to call and interpret this tool correctly.

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 query, store, and country are already well documented. The description adds context about what a seed keyword produces but does not materially extend parameter-level meaning beyond the schema.

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 states a specific verb and resource: research a keyword and related terms, returning up to 10 autocomplete rows with difficulty, popularity, and results count. It explicitly distinguishes this from sonar_keyword_metrics for terms the agent already knows, so the sibling boundary is clear.

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?

It gives explicit when-to-use guidance: find keywords worth targeting, versus using sonar_keyword_metrics for known terms because that is cheaper. It also discloses prerequisites, cost, and latency, which directly affects whether an agent should call it.

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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