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rankedtoday-mcp

rankedtoday-mcp

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github.com/RyanKramerGames & Entertainment0Updated 9w ago
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About rankedtoday-mcp

rankedtoday-mcp gives League of Legends players and their AI agents game-stat estimates and cognitive-readiness references. Its tools make no network calls and show the arithmetic and limits behind estimates.

Key features

  1. 01Estimate MMR from LP gains and losses
  2. 02Calculate games to a target LP
  3. 03Calculate KDA and playtime
  4. 04Assess hardware latency in reaction tests
  5. 05Reference sleep and cognition research
  6. 06Check the ranked season countdown

Use cases

  1. 01Relate LP changes to estimated MMR
  2. 02Plan games needed for a target LP
  3. 03Estimate lifetime account playtime
  4. 04Review research on sleep and cognition in play

MCP support

As an MCP server, it exposes League of Legends calculation and reference tools to clients. Tools are pure functions and require no API key, Riot account, or network calls.

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

mcp.json · Universal config
{
  "mcpServers": {
    "ryankramer-rankedtoday": {
      "command": "uvx",
      "args": [
        "rankedtoday-mcp"
      ]
    }
  }
}
Run commanduvx rankedtoday-mcp

Local servers need a runtime on your machine (e.g. Node.js 18+). Config file locations differ by client; see your client’s docs.

Packages
pypirankedtoday-mcp0.1.0

Tools

8

Saved tool list · updated 2w ago

ParameterTypeRequiredDescription
lp_gainintegerYes
lp_lossintegerYes
current_rankstringNo

Details

From the project README

Ranked Today MCP

League of Legends math and cognitive-readiness reference for AI agents. Estimate MMR from LP flow, project a climb, calculate KDA and lifetime hours, and get the research on sleep and reaction time without the folklore.

No API key. No Riot account. No network calls. Every tool is a pure function and every estimate shows its arithmetic.

Web versions: shouldiplayrankedtoday.com/tools

Install

{
  "mcpServers": {
    "rankedtoday": {
      "command": "uvx",
      "args": ["rankedtoday-mcp"]
    }
  }
}

Or pip install rankedtoday-mcp.

Tools

ToolWhat it does
estimate_mmrInfers whether MMR sits above or below your rank from LP gain/loss asymmetry
climb_calculatorGames required to reach a target LP total, or whether the climb runs backward
kdaKDA with a role-aware read and the winrate caveat
hours_playedLifetime hours from account level, with the math and the error bars
hardware_latency_budgetHow much of a reaction-test score is your monitor and mouse, not you
readiness_referenceWhat the sleep/cognition research supports — and explicitly what it does not
season_countdownDays to a ranked season boundary
rankedtoday_toolsFree cognitive tests and League tools on the web

Design notes

Nothing here pretends to read hidden data. Riot removed public MMR from the API years ago, and there is no lifetime hours counter. estimate_mmr infers from the LP exchange rate and says so; hours_played converts account level and reports plus-or-minus 20% along with what it cannot see. Any tool printing an exact MMR from a summoner name is guessing without telling you.

readiness_reference includes the disconfirming evidence. It lists what the research supports (+49 ms after one all-nighter, 5x more attention lapses, the 516-player rank correlation) and what it does not — including a controlled study where sleep-deprived players' cognition tanked while game outcomes barely moved. Readiness is a probabilistic personal signal, never a win predictor.

climb_calculator will tell you the climb runs backward. Below your breakeven winrate, more games means less LP. It returns that verdict rather than a games-required number, because the honest answer is that this climb does not finish.

Development

git clone https://github.com/RyanKramer/rankedtoday-mcp
cd rankedtoday-mcp
pip install -e .
rankedtoday-mcp

About

Built by Ranked Today — a 3-minute daily cognitive readiness check for League players. Free cognitive tests, no signup.

Not affiliated with or endorsed by Riot Games.

MIT licensed.

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