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Tarune28

ESPN Fantasy Football MCP Server

by Tarune28

get_player_stats

Look up an ESPN Fantasy Football player's season stats, projected points, injury status, and weekly scores by name to assess performance and lineup decisions.

Instructions

Look up a specific player's season stats and current status.

Args: player_name: Full or partial player name.

Returns season totals/averages, projected points, injury status, and available weekly scores.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
player_nameYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

B3.2/5.0
Behavior3/5

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

With no annotations, the description carries the full burden. It usefully discloses the returned content — season totals/averages, projected points, injury status, weekly scores — and the read-only nature of a 'look up' is self-evident. It says nothing about partial-name ambiguity, missing players, or caching/rate behavior.

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?

Short, front-loaded with the purpose, and cleanly split into Args and Returns sections with no filler. The Args block restates a single obvious parameter, a minor redundancy, but overall it is efficient.

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 simple read-only single-parameter lookup with an output schema present, the description covers purpose, the matching semantics of the argument, and the shape of the return. Only edge-case behavior (unknown or ambiguous names) is unaddressed, which is a minor gap given the output schema documents the response.

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 coverage is 0%, so the description must compensate, and it does add real meaning: the parameter accepts a 'Full or partial player name,' which the schema's bare 'Player Name' string does not convey. It still doesn't explain how ambiguous partial matches are resolved, which is the main semantic risk for a single lookup key.

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?

States a specific verb+resource — 'Look up a specific player's season stats and current status' — so an agent knows exactly what it retrieves. It implicitly differentiates from siblings like get_player_schedule and get_team_roster by scope, though it never names an alternative explicitly.

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?

There is no when-to-use guidance, no prerequisites, and no named alternative such as get_player_schedule for schedule data or get_start_sit for lineup decisions. Usage is only inferable from the purpose statement, matching the MID calibration case where context exists but routing is absent.

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