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AlonDrilich

internet-radio-mcp

by AlonDrilich

Top radio stations

top_stations
Read-onlyIdempotent

Find popular internet radio stations by community votes, recent plays, or rising trends; filter by country or genre. Broken streams are excluded.

Instructions

List the most popular internet radio stations: by community votes, by recent clicks (plays), or trending (rising click trend). Optionally limit to one country and/or genre tag. Broken streams are excluded. Station data from the Radio Browser community directory (radio-browser.info, public domain). Stations belong to their broadcasters; 72FM does not own, operate or curate them.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
byNovotes = most voted (default); clicks = most played recently; trending = biggest recent click trend.votes
tagNoOptional genre tag, e.g. "rock".
limitNoMaximum number of stations to return (1-50, default 10).
countrycodeNoTwo-letter ISO 3166-1 alpha-2 country code, e.g. "BR" for Brazil, "JP" for Japan. See list_countries.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
countYes
sourceYes
stationsYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A3.9/5.0
Behavior4/5

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

Annotations already declare readOnly/idempotent/openWorld/destructive=false, so the safety profile is covered. The description adds real behavioral value: broken streams are excluded, results come from the Radio Browser community directory, and ranking options are explained. This goes beyond what annotations provide.

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?

Purpose and ranking modes are front-loaded in the first sentence, and filtering and exclusion behavior follow logically. The closing sentences on data provenance and broadcaster ownership are somewhat tangential to tool selection, but the overall structure remains tight and readable.

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 an output schema present, return-value explanation is unnecessary, and the description covers ranking semantics, optional filters, and stream-quality behavior. An agent has enough to invoke it correctly; only explicit sibling routing is missing.

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 all four parameters (by, tag, limit, countrycode) are already documented in the schema, including the enum meanings and ISO code pattern. The description restates the optional country/genre filtering without adding syntax or format detail beyond the schema, so baseline 3 applies.

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+resource ('List the most popular internet radio stations') and enumerates the three ranking modes. It is clearly distinguishable from siblings like search_stations and get_station, which would serve different intents.

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 when to use it (to browse popularity-ranked stations) and clarifies the three ranking modes, but it never names an alternative such as search_stations or states when this tool is the wrong choice. Usage is inferable rather than explicit.

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