How to Use the The Odds API MCP in Google ADK

Q: How does The Odds API work with the Google ADK?

Your Gemini-powered agent uses the McpToolset wrapper to access all tools from The Odds API. Because of its native BigQuery integration, you can pass the retrieved odds directly into a massive dataset for analysis.

Q: What if my prediction requires data from multiple sports?

You simply call listsports to get all available options, then loop through them using getodds. The agent can hold the context of dozens of different sport analyses simultaneously within its large token capacity.

Q: Can I filter which tools The Odds API makes available?

Yes. When setting up McpToolset, you have an optional toolnames filter. This lets your agent only see, say, getodds and nothing else, keeping the scope tight.

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Setup The Odds API with Google ADK

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Calculate odds for a specific sport.

Use `get_odds` to pull real-time market data from The Odds API into your Google Cloud pipeline. This lets your agent analyze current pricing against historical trends stored in BigQuery. The long context window of Gemini models means you can pass massive amounts of structured and unstructured text—like full league histories—alongside the raw odds for deeper, multi-document reasoning.

Fetch live or past scores.

The `get_scores` tool provides instant game status checks that can be fed directly into a Vertex AI model. This helps your agent contextually adjust predictions based on the current moment of play. Since you're building enterprise agents, the ability to integrate this live data stream with BigQuery makes it easy to track performance over massive time spans.

List all available sports.

When starting a new analysis, call `list_sports` so your agent can map out the full scope of potential betting opportunities. This acts as an initial data inventory for your GCP workflow. If you restrict exposed tools using `tool_names`, you keep the complexity manageable, letting your agent only focus on the specific sports or functions relevant to the current big query.

Setup guide

Set up The Odds API 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 The Odds API 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="The Odds API_agent",
    model="gemini-2.0-flash",
    instruction="You have access to The Odds API 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 The Odds 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 The Odds API MCP in Google ADK

Your Gemini-powered agent uses the `McpToolset` wrapper to access all tools from The Odds API. Because of its native BigQuery integration, you can pass the retrieved odds directly into a massive dataset for analysis.

You simply call `list_sports` to get all available options, then loop through them using `get_odds`. The agent can hold the context of dozens of different sport analyses simultaneously within its large token capacity.

Yes. Gemini models support over 1 million tokens, meaning you aren't limited to small samples. You can process entire season-long odds streams and keep the context intact for final analysis.

Yes. When setting up `McpToolset`, you have an optional tool_names filter. This lets your agent only see, say, `get_odds` and nothing else, keeping the scope tight.

This server deals with publicly available betting odds, scores, and sport metadata. All information is market-derived, not tied to private user accounts or personal identities.

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