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MFL MCP Server

by gsypolt
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TypeScript
Hybrid

Search MFL players

mfl_get_players
Read-onlyIdempotent

Search MFL's NFL player database by name, position, or team to find player IDs, check ages and draft capital, and see fantasy ownership.

Instructions

Search MFL's player database (all NFL players, offense and IDP) by name, position, NFL team, or player ID. Returns ID, name, position, team, age, draft year/round/pick, college, and (by default) which fantasy team in your league owns each player.

Use this to find player IDs for other tools, check ages and draft capital for dynasty decisions, or answer "who owns X?".

Args:

  • name (string, optional): full or partial name, e.g. "bijan" or "St. Brown".

  • positions (string, optional): comma list, e.g. "RB,WR" or "DE,DT,LB".

  • teams (string, optional): comma list of MFL team codes, e.g. "KCC,BUF". "FA" = NFL free agent.

  • player_ids (string, optional): comma list of MFL player IDs.

  • rookies_only (boolean, optional): only players drafted in the selected season.

  • owner (string, optional): only players on this fantasy team: "mine", a franchise ID, or a team name; or "available" for unrostered players.

  • sort ('name' | 'points', default 'name'): 'points' ranks by year-to-date fantasy points under the league's scoring and adds a points column.

  • include_ownership (boolean, default true): add the fantasy owner in this league (one extra API call).

  • league, season: optional (season selects that year's player database).

  • limit (1-200, default 25), offset (default 0).

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

At least one filter is recommended; the full database has thousands of players. Combine filters instead of fetching a big list and filtering it yourself:

  • "My top rookies by points" -> { rookies_only: true, owner: "mine", sort: "points" }

  • "Best available IDP linebackers" -> { positions: "LB", owner: "available", sort: "points" }

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameNoFull or partial player name.
sortNo'points' = year-to-date fantasy points, highest first.name
limitNoMax results to return (1-200, default 25).
ownerNo"mine", a franchise ID, a team name, or "available".
teamsNoComma list of MFL team codes, e.g. "KCC,BUF".
leagueNoWhich league: a configured alias (see mfl_list_leagues), league name, or numeric MFL league ID. Omit for the default league.
offsetNoResults to skip, for paging (default 0).
seasonNoSeason year, e.g. 2025 for last season. Omit for the league's default (usually current) season.
positionsNoComma list, e.g. "QB" or "DE,DT,LB".
player_idsNoComma list of MFL player IDs.
rookies_onlyNoOnly players drafted in the selected season.
response_formatNo'markdown' for readable output (default) or 'json' for structured data.markdown
include_ownershipNoShow which fantasy team owns each player.

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 readOnly/idempotent/non-destructive, so the safety profile is covered. The description adds genuine behavior context beyond that: include_ownership triggers 'one extra API call', sort:'points' adds a points column and ranks under league scoring, and season selects that year's player database.

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 summary sentence followed by returns, then a per-arg list and two example call shapes. The arg bullets largely restate the 100%-covered schema, which is wasted length, but the added examples ('bijan', 'RB,WR') and defaults earn most of it back.

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 no output schema, the description carries the return burden itself and does so: it enumerates returned fields (ID, name, position, team, age, draft year/round/pick, college, ownership), documents defaults for limit/offset/sort/response_format, and warns about the unfiltered result size.

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 baseline is 3; the description still adds value with concrete formats and semantics ('FA' = NFL free agent, owner accepts 'mine'/franchise ID/team name/'available', rookies_only keyed to the selected season). Only mild redundancy with the schema keeps this from a 5.

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 (search) and resource (MFL's player database) with explicit scope: all NFL players, offense and IDP. It also names the return fields and the primary downstream use (find player IDs for other tools), so an agent can distinguish it from mfl_get_roster or mfl_get_free_agents at a glance.

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?

Gives strong when-to-use context: 'at least one filter is recommended; the full database has thousands of players' plus two worked filter combinations for common intents. It falls short of naming when to prefer a sibling such as mfl_get_free_agents, whose purpose overlaps with owner:'available'.

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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