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kienpt91
by kienpt91

ShowMRR search

mrr_search
Read-onlyIdempotent

Search ShowMRR by startup name or keyword to check a company's listed MRR and whether each revenue figure is verified. Use it to validate founder or document revenue claims.

Instructions

Search ShowMRR by startup name or keyword (sends the query to showmrr.com). Use it to look up a company's listed MRR when a founder or document claims a revenue number. No match only means the company is not listed, not that the claim is false. Results state whether each figure is verified.

Input Schema

NameRequiredDescriptionDefault
queryYesStartup name or keyword to search for.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, openWorld), so the description is free to add real context: it discloses that the query leaves the system for showmrr.com and that results carry a verification flag. The key interpretive caveat — no match means unlisted, not false — is exactly the kind of behavioral nuance annotations cannot convey.

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?

Three sentences, each doing distinct work: what it does, when to reach for it, and how to read a negative result. The most decision-relevant caveat is placed last and unburied.

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?

With no output schema, the description usefully tells the agent that returned figures carry verified/unverified status, which is the main thing needed to interpret results. It could still say more about result volume or match granularity (exact vs. fuzzy), leaving a small 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?

Schema coverage is 100% and the single query parameter is already documented with length and character constraints. The description restates "startup name or keyword" without adding syntax, normalization, or matching-behavior detail, so it meets but does not exceed the baseline.

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?

States a specific verb and resource ("Search ShowMRR by startup name or keyword") and scopes it to the external site. An agent can distinguish it from mrr_startup and mrr_leaderboard without opening either schema, since this one is a free-text search rather than a profile or ranking lookup.

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?

Gives a clear trigger: use it to verify a revenue number claimed by a founder or document. It does not explicitly name when to prefer a sibling such as mrr_startup for a known company, so it falls short of full when/when-not routing.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.