How to Use the Apex & Division Stats by TRN MCP in Google ADK

Q: How do I filter tools when using Apex & Division Stats by TRN with Google ADK?

You pass a toolnames list to your McpToolset configuration. This restricts the agent to only the specific Apex or Division functions you want it to execute.

Q: Is it possible to use Apex & Division Stats by TRN to compare Division 2 stats in Google ADK?

You call getdivision2pvpstats to get PvP specific metrics. Your agent can then reason about the player's performance in competitive modes.

Google ADK agents accessing live gaming data through the Apex & Division Stats by TRN MCP Server.

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Connect Apex & Division Stats by TRN MCP to Google ADK

Create your Vinkius account to connect Apex & Division Stats by TRN to Google ADK and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Apex & Division Stats by TRN with Google ADK

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Integrate player stats into Google ADK pipelines

Your Google ADK agents access `search_player` to locate accounts across platforms. It links the correct identifiers before fetching detailed performance records. This setup allows your agents to handle multi-game queries across the ecosystem. You pipe these results directly into your BigQuery data flows.

Run per-legend analysis using Google ADK

The `get_apex_legend_breakdown` tool provides granular kill and win counts. Your agent uses this to generate performance summaries for specific characters. Because your agent handles 1M+ tokens, it keeps track of these legend stats over long conversations. It helps your system provide context-aware feedback to players.

Query global rankings with Google ADK

Use `get_apex_leaderboard` to fetch current global standings. Your agent compares a user's stats against these benchmarks to evaluate skill level. This MCP Server provides the raw data your agent needs to reason about player tiers. It removes the need for custom scraping scripts inside your Google Cloud environment.

Setup guide

Set up Apex & Division Stats by TRN 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 Apex & Division Stats by TRN 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="Apex & Division Stats by TRN_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Apex & Division Stats by TRN tools via MCP.",
    tools=mcp_tools,
)

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Common questions about Apex & Division Stats by TRN MCP in Google ADK

You pass a tool_names list to your McpToolset configuration. This restricts the agent to only the specific Apex or Division functions you want it to execute.

Yes. The toolset supports both Stdio and HTTP transports, making it easy to deploy within your local development or production Google Cloud environments.

You call `get_division2_pvp_stats` to get PvP specific metrics. Your agent can then reason about the player's performance in competitive modes.

The agent maintains the tool outputs in its 1M+ token context window. This allows it to reference multiple match history sessions without losing track of player details.

Data is processed in-memory by your agent during the transaction. We rely on the Vinkius zero-trust sandbox to isolate these requests from other processes.

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