Query League of Legends player stats via Riot Games API
MCP Riot Server lets AI assistants query League of Legends ranks, champion mastery, and match history via Riot's API.
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Why it matters
Retrieve and surface League of Legends player data-including ranks, champion mastery, and match history-through natural language queries to AI assistants, enabling conversational access to Riot Games API endpoints.
Outcomes
What it gets done
Fetch player summaries with level, rank, top champions, and recent matches
Retrieve champion mastery points and rankings for specific players
Pull recent match history with KDA, champions used, and results
Generate detailed match summaries including damage, wards, and performance stats
Source
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Spark does not host a copy of it.
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Capabilities
Tools your agent gets
Fetch player information including summoner name, level, and account details from Riot API.
Retrieve ranked tier, division, and LP information for a specific player.
Fetch champion statistics including win rate, pick rate, and ban rate data.
Retrieve recent match history and game details for a player.
Overview
Riot Games
MCP Riot Server is a community project giving an AI assistant League of Legends data via the Riot Games API, with five tools for player summaries, champion mastery, and match history. It is not affiliated with Riot Games. Use it to answer questions about a League of Legends player's rank, champion mastery, or match performance; requires a Riot Games API key.
What it does
MCP Riot Server is a community-developed MCP server that integrates with the Riot Games API to give an AI assistant League of Legends data through natural language. It exposes five tools: get_player_summary summarizes a player's level, ranked solo tier, top champion masteries, and recent match history; get_top_champions_tool returns a player's top N champions by mastery points; get_champion_mastery_tool returns detailed mastery data for a specific champion; get_recent_matches_tool lists recent matches for a summoner, including the champion played, K/D/A, and result; and get_match_summary returns full match performance stats - KDA, damage, wards, and result - for a given match ID and puuid. It is an open-source project not affiliated with or endorsed by Riot Games; League of Legends is a registered trademark of Riot Games, Inc.
When to use - and when NOT to
Use it to answer natural-language questions about a League of Legends player or match, such as "What's the current rank and top champions of Hide on bush?", "How good is this player with Ahri?", "Show the last 3 matches for this summoner," or "Summarize this match for a given match ID." It requires a Riot Games developer API key; it is scoped to public League of Legends data available through Riot's own API.
Capabilities
get_top_champions_tool returns champions ranked purely by mastery points, useful for identifying a player's strongest picks. get_match_summary needs both a match ID and the player's puuid to scope its stats to that player within the match, distinguishing their performance from other participants in the same game. get_recent_matches_tool's per-match summary (champion, K/D/A, result) gives a quick read on a player's recent form before diving into a single match's full stat line with get_match_summary. The project's own reference list points to the Model Context Protocol Python SDK it is built on and to Riot's Data Dragon static-data documentation, alongside the main Riot Games API docs.
How to install
Clone the repository and install dependencies with uv:
git clone https://github.com/jifrozen0110/mcp-riot.git
cd mcp-riot
# Install dependencies (using uv or pip)
uv sync
Create a .env file with RIOT_API_KEY=your_riot_api_key, obtained from developer.riotgames.com. Register the server in an MCP client's config, for example Claude Desktop's claude_desktop_config.json, with a uv run --env-file command pointing at the project directory and the .env file. Released under the MIT License.
Who it's for
League of Legends players and community developers who want an AI assistant to answer questions about summoner rank, champion mastery, and recent match performance directly from Riot's API.
Source README
MCP Riot Server
MCP-Riot is a community-developed Model Context Protocol (MCP) server that integrates with the Riot Games API to provide League of Legends data to AI assistants via natural language queries.
This project enables AI models to retrieve player information, ranked stats, champion mastery, and recent match summaries.
Disclaimer: This is an open-source project not affiliated with or endorsed by Riot Games. League of Legends® is a registered trademark of Riot Games, Inc.
Demo
✨ Features
🧾 Player Summary
"What's the current rank and top champions of Hide on bush?"
Provides the player's:
- Level
- Ranked Solo Tier
- Top champion masteries
- Recent match history
🔝 Top Champions
"What champions is he best at?"
Returns the top N champions based on mastery points.
🎯 Champion Mastery
"How good is this player with Ahri?"
Returns detailed champion mastery data for a specific champion.
🕹️ Recent Matches
"Show the last 3 matches for this summoner"
Lists recent matches including champion used, K/D/A, and result.
📊 Match Summary
"Summarize this match for a given match ID"
Returns the player’s match stats, such as KDA, damage, wards, and result.
🚀 Quick Start
1. Clone & Install
git clone https://github.com/jifrozen0110/mcp-riot.git
cd mcp-riot
# Install dependencies (using uv or pip)
uv sync
2. Get Your API Key and Set Environment
Create .env file with your Riot API key:
RIOT_API_KEY=your_riot_api_key
You can get your key from https://developer.riotgames.com/
3. Configure MCP Client
Register this server in your MCP client (e.g., Claude for Desktop).
Edit ~/Library/Application Support/Claude/claude_desktop_config.json:
{
"mcpServers": {
"amadeus": {
"command": "/ABSOLUTE/PATH/TO/PARENT/FOLDER/uv",
"args": [
"--directory",
"/ABSOLUTE/PATH/TO/PARENT/FOLDER",
"run",
"--env-file",
"/ABSOLUTE/PATH/TO/PARENT/FOLDER/.env",
"riot.py"
]
}
}
}
Replace
/ABSOLUTE/PATH/TO/PARENT/FOLDER/with the actual path to your project folder.
my case:
{
"mcpServers": {
"amadeus": {
"command": "/Users/jifrozen/.local/bin/uv",
"args": [
"--directory",
"/Users/jifrozen/mcp-riot/src/",
"run",
"--env-file",
"/Users/jifrozen/mcp-riot/.env",
"server.py"
]
}
}
}
🛠️ Tools
The following tools will be exposed to MCP clients:
get_player_summary
Summarizes level, rank, top champions, and recent matches.
get_top_champions_tool
Returns top champions by mastery points.
get_champion_mastery_tool
Returns mastery details for a specific champion.
get_recent_matches_tool
Returns recent matches for the given summoner.
get_match_summary
Returns match performance stats for a given match ID and puuid.
📚 References
📝 License
MIT License © 2025 jifrozen0110
FAQ
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