How to Use the AeroDataBox MCP in Google ADK

Q: How do I configure AeroDataBox with Google ADK in my enterprise pipeline?

Install the ADK package and initialize the McpToolset using the Streamable HTTP parameters pointing to your Vinkius server. This MCP integration immediately grants your LlmAgent instance access to live tools like getairlinefleet and getflighthistory.

Q: How do I find the closest airport to an IP address?

Your agent can call getairportsbyip directly. This returns the nearest airports, which can then be used to query local delay stats using getairportdelays.

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Connect AeroDataBox MCP to Google ADK

Create your Vinkius account to connect AeroDataBox 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 AeroDataBox with Google ADK

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Long-Context Airport Analysis with Google ADK

Tap into Gemini's massive context window to process complete airport flight information displays. Your agent can ingest raw arrival and departure data from `get_fids_absolute` and cross-reference it with historical trends. No more worrying about token limits when analyzing busy international hubs. The agent can combine this with operational physical profiles from `get_airport_runways`. By running these tools through the MCP Server, your Google ADK agent builds a complete operational picture of airport capacity on the fly.

Fusing BigQuery Data with Live Flights

Combine your internal enterprise logistics databases with live flight updates. Your agent can pull historical shipping records from BigQuery and immediately match them against active flights using `get_flight_by_date`. This lets you track high-value cargo delays as they happen. If a delay is detected via `get_airport_delays`, the agent can calculate new ETA vectors using `get_distance_time`. This direct connection between Google Cloud storage and live MCP tools keeps your supply chain data accurate.

Global Delay Forecasting

Run global operational risk assessments directly from your enterprise agent. The toolset exposes `get_global_delays` and `get_global_delays_historical` to feed your predictive models. Your Google ADK agent can process these global metrics to highlight systemic bottleneck patterns. This setup runs securely on Google Cloud infrastructure. You can restrict which tools are exposed to the agent by applying a tool name filter to your MCP toolset, ensuring the agent only accesses authorized endpoints.

Setup guide

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

Install the ADK package and initialize the `McpToolset` using the Streamable HTTP parameters pointing to your Vinkius server. This MCP integration immediately grants your `LlmAgent` instance access to live tools like `get_airline_fleet` and `get_flight_history`.

Yes, you can use the ADK's built-in tool name filter when defining your toolset. If you only want your agent checking schedules, restrict the exposure to `get_fids_relative` and `get_flight_by_date`, blocking access to billing tools like `refill_alert_balance`.

Gemini's long-context capabilities allow the agent to ingest massive payloads from `get_fids_absolute` without truncation. The ADK handles the transport layer smoothly, passing raw JSON structures directly into the model's active memory for complex reasoning.

Your agent can call `get_airports_by_ip` directly. This returns the nearest airports, which can then be used to query local delay stats using `get_airport_delays`.

Your AeroDataBox credentials and flight query history are isolated within a dedicated V8 sandbox. Google ADK routes these requests through secure HTTP transport layers, ensuring your operational data and API tokens remain private.

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