How to Use the BallDontLie MCP in Google ADK

Q: Can I restrict which BallDontLie tools my Google ADK agent uses?

Yes. The ADK lets you pass an optional toolnames list. You can limit the agent to just getgamedetails if you only want it analyzing specific matches.

Ground your Google ADK enterprise agents with real-time NBA data and massive context windows.

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Connect BallDontLie MCP to Google ADK

Create your Vinkius account to connect BallDontLie 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 BallDontLie with Google ADK

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Perplexity

Analyze entire seasons with this MCP Server

Gemini's massive context window eats huge datasets for breakfast. Feed it an entire season of box scores using `list_games` and let the model find hidden trends. You do not have to chunk the data. The ADK natively ties this into your Google Cloud infrastructure. Pull raw numbers via `list_player_stats`, dump them into BigQuery, and run complex SQL joins against your proprietary sports data.

Deep dive into player performance

Building a scouting agent requires specific, targeted queries. Your Gemini agent can execute `get_player_details` to grab the baseline bio, then immediately fire off `get_season_averages` to see how they perform on the road. You control exactly which tools the agent sees. Use the tool_names filter in your McpToolset config to restrict access to just player data if you want to keep the agent focused.

Track team matchups and history

Real sports analytics means understanding team dynamics over time. Call `list_teams` to build your baseline index, then iterate through `get_team_details` to map out division hierarchies. Combine this with Vertex AI. Your agent grabs the raw API responses, formats them into training examples, and fine-tunes a custom prediction model on Google Cloud.

Setup guide

Set up BallDontLie 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 BallDontLie 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="BallDontLie_agent",
    model="gemini-2.0-flash",
    instruction="You have access to BallDontLie tools via MCP.",
    tools=mcp_tools,
)

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Common questions about BallDontLie MCP in Google ADK

Set up an McpToolset using StreamableHttpServerParameters with your Vinkius endpoint. Then pass that toolset directly to your LlmAgent initialization.

Yes. The ADK lets you pass an optional tool_names list. You can limit the agent to just get_game_details if you only want it analyzing specific matches.

It works perfectly for this. You can dump hundreds of JSON responses from list_player_stats straight into the prompt. Gemini holds it all in memory for deep reasoning.

That is the main advantage of this setup. Your agent fetches the NBA stats and can immediately write those records to your BigQuery tables for long-term storage.

Vinkius isolates every request in an ephemeral V8 sandbox. Your Gemini prompts and the resulting MCP data are processed and immediately wiped from memory.

Use it with your favorite AI tools

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