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MFL MCP Server

by gsypolt
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Hybrid

Get MFL roster(s)

mfl_get_roster
Read-onlyIdempotent

Retrieve fantasy football rosters for MyFantasyLeague franchises, including player names, positions, NFL teams, status, and salary, filtered by season, week, position, or roster status.

Instructions

Get the players on a franchise's roster (or every roster in the league), with player name, position (offense and IDP), NFL team, age, roster status (Active, Taxi, IR), and salary/contract fields when the league uses them.

Defaults to YOUR franchise when one is configured. Use franchise="all" to see every team (useful for "who owns X", trade targets, or league-wide positional depth).

Args:

  • league, season: optional. Use season to see a previous season's final rosters.

  • franchise (string, optional): "mine" (default), "all", a franchise ID like "0007", or a team/owner name.

  • week (number, optional): roster as of a specific week.

  • position (string, optional): only show this position, e.g. "QB", "LB", "S".

  • status (string, optional): 'active' | 'taxi' | 'ir' to filter roster status.

  • response_format: 'markdown' (default) or 'json'.

Examples:

  • "Show my roster" -> {}

  • "Who has the most linebackers?" -> { franchise: "all", position: "LB" }

  • "What did my taxi squad look like last year?" -> { season: 2025, status: "taxi" }

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
weekNoNFL week number (1-22). Omit for the current week.
leagueNoWhich league: a configured alias (see mfl_list_leagues), league name, or numeric MFL league ID. Omit for the default league.
seasonNoSeason year, e.g. 2025 for last season. Omit for the league's default (usually current) season.
statusNoFilter by roster status.
positionNoFilter to one position, e.g. "RB" or "LB".
franchiseNo"mine" (default), "all", a franchise ID, or a team/owner name.
response_formatNo'markdown' for readable output (default) or 'json' for structured data.markdown

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint/idempotentHint/openWorldHint and destructiveHint=false, so the safety profile is covered. The description adds real behavioral context beyond that: the franchise defaulting rule, the season-override semantics for retrieving historical rosters, and the conditional presence of salary/contract fields ('when the league uses them').

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 purpose and default behavior, and the examples earn their space by showing argument composition. The Args block largely restates the JSON schema descriptions verbatim, which is mild redundancy that keeps it from a 5.

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?

With 7 optional parameters, no output schema, and a conditional-field payload, the description compensates by enumerating the returned fields and documenting defaults and history access. Nothing needed to call it correctly is missing.

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?

Schema coverage is 100%, so the baseline is 3, but the description goes further by decoding the polymorphic 'franchise' parameter into four accepted forms and by mapping natural-language queries to concrete argument combinations in the examples ('Who has the most linebackers?' -> { franchise: 'all', position: 'LB' }).

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?

Specific verb+resource ('Get the players on a franchise's roster (or every roster in the league)') plus an enumeration of the exact returned fields (name, position, NFL team, age, roster status, salary/contract). The scope statement implicitly separates it from siblings like mfl_get_players (whole player universe) and mfl_get_free_agents (unrostered players).

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?

States the default behavior ('Defaults to YOUR franchise when one is configured') and gives explicit conditions selecting alternatives ('Use franchise="all" to see every team' for ownership questions, trade targets, positional depth; 'Use season to see a previous season's final rosters'). No explicit exclusions against sibling tools, but the usage context 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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