Skip to main content
Glama
DanielTomaro13

sportsdata-mcp

mlb_player_stats

Read-onlyIdempotent

Retrieve a player's MLB stats by type (season, career, year-by-year, game log) and category (hitting, pitching, fielding). Specify player ID, season, and category to get structured splits with team and league details.

Instructions

One player's stats — by type (season / career / yearByYear / gameLog) and group (hitting/pitching/fielding).

Returns: {stats:[{type, group, splits:[{season, stat:{...}, team, league}]}]}

Auth: none needed.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
groupNohitting | pitching | fielding.hitting
statsNoseason | career | yearByYear | gameLog | statSplits.season
seasonNoSeason year (for season/gameLog types).
personIdYesPlayer id. Required — part of the URL path.
Behavior4/5

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

Annotations already declare readOnlyHint, openWorldHint, and idempotentHint, so the description only needs to add context. It adds 'Auth: none needed' and specifies the return shape, which is valuable beyond the annotations. No contradictions detected.

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?

The description is two sentences: the first front-loads the core purpose and options, the second provides the return format and auth requirement. Every word earns its place; no redundancy or fluff.

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?

Despite having no output schema, the description includes a return shape ({stats:[{type, group, splits...}]}), which compensates. It covers all parameter dimensions and scopes the tool to a single player, though it lacks examples or edge-case details like default season behavior.

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 parameters are well-documented. The description adds a small connection between type/group and the return structure (splits with season/team/league), but does not substantially extend the schema's explanations.

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 clearly states 'One player's stats' and enumerates selectable types (season/career/yearByYear/gameLog) and groups (hitting/pitching/fielding), making its purpose specific. It distinguishes from sibling tools like mlb_player (player info) and mlb_player_game_stats (game-specific stats) by covering multiple stat types, though it lacks an explicit verb like 'get'.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no explicit guidance on when to use this tool versus alternatives. The type and group parameters imply use cases, but no comparison to sibling tools like mlb_player_game_stats or mlb_team_stats is given, leaving the agent to infer the boundary.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/DanielTomaro13/sportsdata-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server