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Nba Get Teams

nba_get_teams
Read-onlyIdempotent

Get all 30 NBA teams with full names, abbreviations, conference, and division. Use to find team info or prepare for get_games queries. Requires a free BallDontLie API key.

Example tool call

This call uses example arguments supplied in the tool’s input schema.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "nba_get_teams"
  }
}

Input Schema

NameRequiredDescriptionDefault
_apiKeyYesBallDontLie API key (free tier: https://www.balldontlie.io/)

Output Schema

NameRequiredDescriptionDefault
teamsYesList of all NBA teams
totalYesTotal number of NBA teams

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint and openWorldHint, so the description wisely doesn't restate safety. It adds real behavioral context: the result set is a fixed, complete list of 30 teams, and a free BallDontLie API key is an auth prerequisite -- something annotations cannot express.

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?

Two short sentences, front-loaded with what is returned and followed by usage and prerequisites. Every clause carries information; there is no filler or repetition of the tool name.

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 single-parameter read of a fixed collection with an output schema, this covers what is returned, the size of the result set, the intended use, and the auth requirement. Return-value details are correctly left to the output schema.

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?

There is a single parameter and the schema documents it at 100% coverage, including the signup URL. The description's mention of an API key requirement only echoes the schema's _apiKey description rather than adding format or sourcing detail, so baseline 3 applies.

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 opens with a specific verb and resource ('Get all 30 NBA teams') and enumerates the returned fields (names, abbreviations, conference, division). It is immediately distinguishable from players/games siblings by naming 'teams' explicitly, though it doesn't contrast itself against the other NBA tools beyond a passing reference to get_games.

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?

'Use to find team info or prepare for get_games queries' gives a concrete use case and a workflow link to a sibling. It has no explicit when-not or exclusion guidance, and doesn't say what to do if the API key is missing, but the intended usage is clear.

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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