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trustmrr_leaderboard

Retrieve the top 100 startups from the public TrustMRR leaderboard, ranked by your chosen metric such as MRR, revenue, growth, or traffic, with payment-verified figures.

Instructions

Get TrustMRR revenue leaderboard. Returns the top 100 startups ranked by the selected metric from the public TrustMRR leaderboard. Revenue and MRR figures are verified through supported payment providers.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
metricNoLeaderboard metric to rank by (default mrr)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv1.17.5
    • addedInput schema / properties / metric / enum
      Added value: +[
+  "mrr",
+  "last_30_days_revenue",
+  "all_time_revenue",
+  "growth",
+  "traffic",
+  "revenue_per_visitor"
+]
  2. Addedv1.5.0

TDQS

B3.4/5.0
Behavior3/5

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

With no annotations provided, the description carries the burden of behavior disclosure. It reveals that data is verified through payment providers and that results are limited to top 100, but does not mention pagination, sorting behavior, or whether metrics require specific filters or have edge cases.

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 a single, concise paragraph with no fluff. It front-loads the core purpose ('Get TrustMRR revenue leaderboard') and then specifies key details (top 100, metric selection, verified data). Slightly dense but efficient.

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

Completeness3/5

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

Given the simplicity (one parameter) and no output schema, the description covers the essential functionality. However, it lacks guidance on what the response looks like, how to interpret results, or any rate limits; these gaps are minor given the tool's narrow scope, but a more complete description would mention output format.

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 description adds context by mentioning the metric ranks startups, but the schema already enumerates the six metric options with descriptions. Coverage is 100%, so the description does not need to elaborate much; however, it does not clarify default behavior or the meaning of each metric beyond what the schema states.

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 tool fetches a revenue leaderboard and ranks the top 100 startups by a selected metric. It distinguishes itself from the sibling trustmrr_startup by focusing on the leaderboard rather than individual startup details.

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?

The description implies usage for leaderboard queries but does not explicitly state when to choose this over trustmrr_startups or trustmrr_startup. No alternative tools are named, leaving the agent to infer context from the name and description.

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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