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joeyaflores

revenuecat-charts-mcp

by joeyaflores

Get Subscription Overview

rc_get_overview
Read-onlyIdempotent

Get a real-time snapshot of key subscription health metrics like MRR, active subscriptions, and revenue. Return current state without specifying a date range.

Instructions

Get a real-time snapshot of key subscription health metrics. No date range needed — returns current state.

Args:

  • api_key (string): RevenueCat secret API key starting with "sk_"

  • project_id (string, optional): RevenueCat project ID (e.g., "proj058a6330"). Auto-detected if omitted.

Returns: Markdown summary with: Active Trials, Active Subscriptions, MRR ($), Revenue (28d), New Customers (28d), Active Users (28d), Transactions (28d).

Examples:

  • "What's my current MRR?" -> call with just api_key

  • "Give me a subscription health check" -> call with just api_key

  • "How many active subscribers do I have?" -> call with just api_key

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
api_keyYesRevenueCat secret API key (starts with sk_)
project_idNoRevenueCat project ID (e.g., 'proj058a6330'). Auto-detected if omitted.
Behavior5/5

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

Annotations already declare readOnlyHint and idempotentHint, and the description adds the return format (Markdown summary with specific metrics) and auto-detection of project_id. It also discloses that api_key is required and that project_id is auto-detected, which is behavioral context beyond the schema.

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 well-structured with a clear one-sentence summary, followed by Args, Returns, and Examples sections. No unnecessary fluff; every section adds value and it is front-loaded with the main purpose.

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?

For a simple read-only tool with two parameters and no output schema, the description explains what it returns (specific metrics list), how to call it, and provides three usage examples. It is complete enough for an agent to select and invoke correctly.

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

Parameters4/5

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

The input schema already fully describes both parameters (100% coverage), and the description reinforces api_key format and adds auto-detection behavior for project_id with an example. This adds meaningful context beyond the schema's static description.

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 uses the specific verb 'Get' and resource 'overview' of 'subscription health metrics', clearly distinguishing it from sibling tools like rc_list_metrics and rc_get_chart. It states it returns a real-time snapshot without a date range, which is a unique scope.

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

Usage Guidelines4/5

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

It provides clear context by stating 'No date range needed — returns current state' and gives example questions for when to call it. However, it does not explicitly mention when not to use it or direct to alternatives like rc_list_metrics or rc_get_chart, so there are no explicit exclusions.

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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