Crawlora MCP

mlb_standings

Read-only

Returns American League and National League standings, including source-provided expected, home/away, last-ten, ranking, and elimination fields when available, using any supported standings type returned by mlb_discovery. season: Optional. Four-digit season; defaults to the current year. Use espn_standings to retrieve eSPN standings.

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": "mlb_standings"
  }
}

Input Schema

Name	Required	Description
`date`	No	Optional snapshot date in YYYY-MM-DD format; returns standings as of that date.
`type`	No	Optional. One of regularSeason, wildCard, springTraining. Defaults to regularSeason.
`season`	No	Optional. Four-digit season; defaults to the current year.

Output Schema

Name	Required	Description	Default
`data`	Yes	The tool result payload (shape varies per tool; see each tool's docs resource).

Schema Changelog

Changes observed during successful MCP inspections.

First observedOct 5, 2026

TDQS

A3.9/5.0

Behavior3/5

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

Annotations already declare readOnlyHint=true and openWorldHint=true, so the safety profile is covered. The description adds that certain fields (expected, home/away, last-ten, ranking, elimination) appear only 'when available', which is mildly useful conditional-return context, but an output schema exists so return detail is largely handled elsewhere.

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?

Front-loaded with the core purpose and kept to a few sentences with no wasted padding. The middle clause enumerating conditional fields is slightly dense but still earns its place by signaling variability in the response.

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 100% schema coverage, an output schema, and read-only/open-world annotations, the description covers the remaining need: what standings are returned, the allowed type source, and the sibling alternative. Only explicit when-not guidance 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% and all three parameters are documented in the schema. The description only restates the season default, adding no syntax or format detail beyond what the schema already provides, so the 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 ('Returns') and resource ('American League and National League standings') with the source of the standings type made explicit. An agent can distinguish it from espn_standings and the other mlb_* siblings without opening the schema.

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?

Explicitly names the alternative ('Use espn_standings to retrieve eSPN standings') and ties the standings type to mlb_discovery. It gives clear routing context but does not state when NOT to use this tool (e.g. in-season vs historical).

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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