How to Use the Riot Games MCP in Google ADK

Q: Can I store Riot Games match histories fetched via Google ADK into BigQuery?

Yes. Your agent can use getmatch to retrieve full game details, and you can write a simple Python function within your ADK pipeline to write that JSON directly to your BigQuery tables.

Q: How do I restrict which Riot Games tools are exposed to my Google ADK agent?

Use the toolnames filter when instantiating your McpToolset. This lets you expose only high-level tools like getleagueentries while hiding administrative or static tools.

Q: Does Google ADK support real-time Riot Games spectator lookups?

Yes, the getactivegame tool retrieves live spectator data via our MCP integration. Your Gemini agent can parse this information instantly to identify champion matchups and lane configurations.

Q: How do I handle regional routing for international players?

Tools like getmatchids require regional parameters such as americas or europe. Your agent passes these parameters directly through the ADK tool call based on the player's account region.

Connect Riot Games live match data to your Google ADK pipelines with this MCP Server.

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Connect Riot Games MCP to Google ADK

Create your Vinkius account to connect Riot Games to Google ADK — we handle the hosting, security, and runtime updates so you don't have to. No server setup required.

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Setup Riot Games with Google ADK

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Enterprise Match Analysis with Google ADK

The `get_match` tool injects raw post-game telemetry directly into your Google ADK pipeline, letting Gemini ingest complex League JSON structures across thousands of tokens. Look, this enables your Google ADK agent to run deep-dive post-mortems on team fights and objective control, storing the structured output in BigQuery. Because Gemini handles massive contexts, you can feed multiple League match objects from `get_match_ids` into a single prompt. The MCP Server ensures every stat, from gold earned to damage dealt, is delivered to Google Cloud without truncation.

Live Lobby Scouting at Scale

The `get_active_game` tool pulls real-time lobby details, including runes and champion bans, into your Google ADK agent via MCP. This lets your Google ADK system cross-reference live player stats with historical performance data stored in your enterprise warehouse. By calling `get_league_entries` alongside the active game data, your Gemini-powered agent can predict League game outcomes or suggest counter-picks. Honestly, the Google ADK toolset configuration allows you to filter out unused endpoints to keep your tool list clean.

Global Player Profiling via MCP Server

The `get_account_by_riot_id` tool resolves Riot IDs into PUUIDs, which are essential for tracking player progression across different regional servers using Google ADK. This MCP Server handles the regional routing under the hood, letting your Google ADK agent query players from br1 to kr without manual configuration. Once the PUUID is resolved, your Google ADK agent can pull mastery data using `get_champion_masteries` to map player habits. It is a direct, code-free way to build a global League of Legends database on Google Cloud.

Setup guide

Set up Riot Games MCP in Google ADK

Prerequisites

Python 3.10+ installed
google-adk package (pip install google-adk)
Active Vinkius subscription with a valid endpoint token

1

Install Google ADK

Run pip install google-adk to install the Agent Development Kit. MCP support is included via the McpToolset class.
2

Connect via SSE transport

Use McpToolset.from_server() with SseServerParams pointing to your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Create an LlmAgent

Pass the returned mcp_tools list directly to LlmAgent(tools=mcp_tools). The ADK maps each MCP tool to a native Gemini function call — no manual schema definitions required.
4

Run with any Gemini model

The agent works with any Gemini model (gemini-2.0-flash, gemini-2.5-pro, etc.). Copy the full example on the right to get started with Riot Games tools in your ADK agent.

agent.py

from google.adk.agents import LlmAgent
from google.adk.tools.mcp_tool.mcp_toolset import McpToolset
from google.adk.tools.mcp_tool.mcp_session_manager import SseServerParams

# Connect to the MCP via SSE
mcp_tools, exit_stack = await McpToolset.from_server(
    connection_params=SseServerParams(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    )
)

# Create your agent with auto-discovered tools
agent = LlmAgent(
    name="Riot Games_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Riot Games tools via MCP.",
    tools=mcp_tools,
)

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Riot Games API. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about Riot Games MCP in Google ADK

Yes. Your agent can use `get_match` to retrieve full game details, and you can write a simple Python function within your ADK pipeline to write that JSON directly to your BigQuery tables.

Use the `tool_names` filter when instantiating your `McpToolset`. This lets you expose only high-level tools like `get_league_entries` while hiding administrative or static tools.

Yes, the `get_active_game` tool retrieves live spectator data via our MCP integration. Your Gemini agent can parse this information instantly to identify champion matchups and lane configurations.

Tools like `get_match_ids` require regional parameters such as americas or europe. Your agent passes these parameters directly through the ADK tool call based on the player's account region.

Your developer key is stored securely in the Vinkius V8 Isolate Sandbox. The agent communicates via an ephemeral, authenticated HTTP tunnel, meaning your raw API credentials never enter your local environment or Google Cloud logs.

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