How to Use the CarAPI MCP in Google ADK

Ground Gemini models with real-time CarAPI specifications using the Google ADK framework.

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Connect CarAPI MCP to Google ADK

Create your Vinkius account to connect CarAPI 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 CarAPI with Google ADK

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Ground Gemini models with real-time CarAPI specs

`get_vehicles` feeds raw automotive specs directly into your Gemini long-context window. Google ADK routes the tool output so your model can compare thousands of trims and MSRPs without hitting context limits. By exposing `get_makes` and `get_models`, you let your enterprise agent query the MCP database instead of guessing. The agent maps user requests to exact database records.

Connect Google ADK workflows to automotive data

This MCP Server exposes tools like `get_engines` and `get_bodies` to let your agent build structured vehicle profiles. You can feed this structured data directly into BigQuery or Vertex AI pipelines. You register the tools using the McpToolset class inside your Python code. The ADK takes care of the transport details, whether you run over HTTP or a standard stdio pipe.

Filter search parameters to optimize token usage

The `get_years` tool retrieves valid production years so your agent does not waste tokens searching empty databases. Narrowing the search early keeps your API costs low. Using `get_drives` and `get_transmissions` allows the model to pinpoint specific drivetrain configurations. Your enterprise agents can build highly specific vehicle comparison tables in seconds.

Setup guide

Set up CarAPI 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 CarAPI 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="CarAPI_agent",
    model="gemini-2.0-flash",
    instruction="You have access to CarAPI 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 CarAPI. 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 CarAPI MCP in Google ADK

Initialize the MCP toolset with your Vinkius HTTP endpoint and pass it to your LlmAgent. The framework registers the eight automotive tools, making them immediately available to Gemini.

Yes, you can pass a list of allowed tool names to the McpToolset constructor. This lets you limit the agent to only `get_vehicles` or `get_makes` if you want to control its actions.

Gemini models use their massive context window to ingest the full JSON payload from `get_vehicles`. The model can analyze dozens of trims, engine specs, and MSRPs simultaneously without losing track of the details.

Yes, the server runs in a secure V8 Isolate sandbox on Vinkius. Your connection uses a single token, keeping your backend credentials hidden from the client agent.

The server only processes public automotive specs, car makes, and model years. No user-identifying data or private cloud database schemas are ever exposed to the sandbox during these queries.

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