Mcp Riot Server

What is Mcp Riot Server about?

Mcp Riot Server enables AI models to query Riot Games’ public API for detailed League of Legends data such as player rank, top champions, mastery information, recent matches, and match‑by‑match performance.

How to use Mcp Riot Server?

1. Clone the repository and install dependencies (recommended using uv).
2. Create a .env file and set RIOT_API_KEY with a key obtained from the Riot Developer Portal.
3. Register the server in your MCP‑compatible client (e.g., Claude for Desktop) by adding the command and arguments shown in the README.
4. Run the server – the MCP client will now be able to invoke the exposed tools via natural language.

Key features of Mcp Riot Server

• get_player_summary – level, rank, top champions, recent matches.
• get_top_champions_tool – list of champions ordered by mastery points.
• get_champion_mastery_tool – detailed mastery stats for a specific champion.
• get_recent_matches_tool – recent match list with champion, K/D/A, result.
• get_match_summary – comprehensive stats for a given match ID and puuid.

Use cases of Mcp Riot Server

• AI‑driven game coaching: ask an assistant “What is my current rank and top champions?” and receive a concise summary.
• Content generation: automatically generate match recaps for stream overlays or blogs.
• Stat tracking bots: integrate with Discord/Slack to report a player’s recent performance on demand.
• Research & analytics: pull large batches of match data for statistical analysis without manual API calls.

FAQ from the Mcp Riot Server

• Do I need a paid Riot API key? No, a free developer key works, but it is rate‑limited.
• Which regions are supported? All regions covered by the Riot API; the server forwards the appropriate endpoint based on the summoner’s region.
• Can I deploy this on a cloud server? Yes, run the Python process on any VM/container and expose the MCP port.
• Is the project affiliated with Riot Games? No, it is community‑maintained and not endorsed by Riot.
• What Python version is required? Python 3.10+ is recommended.

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.

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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.

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🚀 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"
            ]
        }
    }
}

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🛠️ 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.

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📚 References

• Model Context Protocol Python SDK
• Riot Games API Docs
• Data Dragon (static data)

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📝 License

MIT License © 2025 jifrozen0110