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Aptabase MCP Server

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by aptabase

get_metrics

Retrieve key app metrics like daily users, sessions, events, and average duration over a chosen period, with filters and previous-period comparison.

Instructions

Key metrics for an app over a period: daily users, sessions, events, avg duration. Includes previous-period comparison when a date range is set.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
appIdYesAptabase app id (from list_apps)
osNameNoFilter by OS name (e.g. iOS, Android, macOS)
periodNoDashboard period preset. Prefer this over startDate/endDate. Defaults to 24h for stats tools when neither period nor dates are set.
endDateNoISO end datetime (use with startDate if not using period)
buildModeNoRelease or debug build mode (debug queries appId_DEBUG)release
eventNameNoFilter by event name
startDateNoISO start datetime (use with endDate if not using period)
appVersionNoFilter by app version
countryCodeNoFilter by ISO country code
deviceModelNoFilter by device model
granularityNoOverride bucket size; auto-derived from period/range when omitted
Behavior3/5

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

No annotations are provided, so description carries full burden. It discloses that previous-period comparison is included when a date range is set, adding behavioral context beyond the schema. However, it does not detail how filters interact with the comparison or describe output structure.

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?

Single sentence, 18 words, front-loaded with tool's purpose and return types. 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 11-param tool with no output schema, the description summarizes return values (daily users, sessions, events, avg duration) and conditional comparison. It gives a sufficient overview, though more detail on time-series vs aggregate output could help.

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%; description adds no specific parameter semantics beyond what schema provides. The mention of 'date range' aligns with startDate/endDate but adds no new detail.

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?

Description clearly states 'Key metrics for an app over a period' and enumerates specific metrics (daily users, sessions, events, avg duration). It distinguishes from ranking tools but does not explicitly contrast with get_periodic_stats.

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?

Description implies usage for overview key metrics but does not provide explicit guidance on when to choose this over sibling tools like get_periodic_stats or get_top_events. No exclusions or alternatives mentioned.

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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