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MLB Stats MCP

MLB Stats MCP

by prnv-13
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

list_teams

Read-onlyIdempotent

Retrieve all 30 MLB teams with their IDs, abbreviations, league, division, and ballpark details to quickly identify and map teams for stats queries.

Instructions

List all 30 MLB teams with their ids, abbreviations, league, division and ballpark.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

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

Input Schema

NameRequiredDescriptionDefault

No arguments

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.7/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint and openWorldHint, so the safety profile is covered. The description adds the shape of the data (30 fixed teams with identifiers and ballpark), but says nothing about freshness, season scope, or any auth/rate considerations that openWorldHint might imply.

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?

A single front-loaded sentence with zero filler, leading with the verb and the count (30) before detailing fields. Nothing needs trimming and nothing essential is buried.

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?

For a zero-parameter list tool with an output schema and full annotation coverage, the description is essentially sufficient. The only minor gap is that it does not state whether the team set or ballpark data is season-dependent.

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 tool takes zero parameters, so there is nothing for the description to disambiguate and the baseline of 4 applies. The field list it does provide describes outputs rather than inputs, which is harmless but does not raise it further.

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 states a specific verb and resource ("List all 30 MLB teams") and enumerates the fields returned (ids, abbreviations, league, division, ballpark), so the agent knows exactly what it gets. It does not explicitly contrast itself with siblings like get_standings or get_team_roster, which keeps it from a 5.

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 gives no explicit when-to-use or when-not-to-use guidance, and it names no alternatives. Usage is only implied by the resource name: an agent must infer that this is the lookup tool for team metadata rather than statistics or rosters.

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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