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Netrows MCP Server for Google ADK 12 tools — connect in under 2 minutes

Built by Vinkius GDPR 12 Tools SDK

Google Agent Development Kit (ADK) is Google's framework for building production AI agents. Add Netrows as an MCP tool provider through Vinkius and your ADK agents can call every tool with full schema introspection.

Vinkius supports streamable HTTP and SSE.

python
from google.adk.agents import Agent
from google.adk.tools.mcp_tool import McpToolset
from google.adk.tools.mcp_tool.mcp_session_manager import (
    StreamableHTTPConnectionParams,
)

# Your Vinkius token. get it at cloud.vinkius.com
mcp_tools = McpToolset(
    connection_params=StreamableHTTPConnectionParams(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
    )
)

agent = Agent(
    model="gemini-2.5-pro",
    name="netrows_agent",
    instruction=(
        "You help users interact with Netrows "
        "using 12 available tools."
    ),
    tools=[mcp_tools],
)
Netrows
Fully ManagedVinkius Servers
60%Token savings
High SecurityEnterprise-grade
IAMAccess control
EU AI ActCompliant
DLPData protection
V8 IsolateSandboxed
Ed25519Audit chain
<40msKill switch
Stream every event to Splunk, Datadog, or your own webhook in real-time

* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About Netrows MCP Server

Connect your Netrows Aviation API flight tracking platform to any AI agent and take full control of real-time flight monitoring, aircraft intelligence, airport operations, and airline schedule analysis through natural conversation.

Google ADK natively supports Netrows as an MCP tool provider. declare Vinkius Edge URL and the framework handles discovery, validation, and execution automatically. Combine 12 tools with Gemini's long-context reasoning for complex multi-tool workflows, with production-ready session management and evaluation built in.

What you can do

  • Flight Search — Find active and recent flights by flight number, callsign, or origin-destination airport pair
  • Flight Details — Get comprehensive flight information including airports, times, aircraft, and status
  • Real-Time Tracking — Monitor live flight positions with coordinates, altitude, speed, and heading
  • Aircraft Registry — Look up aircraft specifications, ownership, registration, and fleet details
  • Fleet Analysis — Search all aircraft operated by specific airlines or aviation companies
  • Airport Intelligence — Query airport static data, codes, locations, and timezone information
  • Airport Activity — Monitor all arriving and departing flights at any airport worldwide
  • Airport Search — Find all airports serving a specific city or metropolitan area
  • Flight Schedules — Access complete flight schedules between any two airports
  • Airline Monitoring — Track all active flights by airline with real-time operational data
  • Airline Profiles — Get airline company information including fleet size, hubs, and destinations
  • Account Usage — Monitor your API credit consumption and remaining quota

The Netrows MCP Server exposes 12 tools through the Vinkius. Connect it to Google ADK in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect Netrows to Google ADK via MCP

Follow these steps to integrate the Netrows MCP Server with Google ADK.

01

Install Google ADK

Run pip install google-adk

02

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

03

Create the agent

Save the code above and integrate into your ADK workflow

04

Explore tools

The agent will discover 12 tools from Netrows via MCP

Why Use Google ADK with the Netrows MCP Server

Google ADK provides unique advantages when paired with Netrows through the Model Context Protocol.

01

Google ADK natively supports MCP tool servers. declare a tool provider and the framework handles discovery, validation, and execution

02

Built on Gemini models, ADK provides long-context reasoning ideal for complex multi-tool workflows with Netrows

03

Production-ready features like session management, evaluation, and deployment come built-in. not bolted on

04

Seamless integration with Google Cloud services means you can combine Netrows tools with BigQuery, Vertex AI, and Cloud Functions

Netrows + Google ADK Use Cases

Practical scenarios where Google ADK combined with the Netrows MCP Server delivers measurable value.

01

Enterprise data agents: ADK agents query Netrows and cross-reference results with internal databases for comprehensive analysis

02

Multi-modal workflows: combine Netrows tool responses with Gemini's vision and language capabilities in a single agent

03

Automated compliance checks: schedule ADK agents to query Netrows regularly and flag policy violations or configuration drift

04

Internal tool platforms: build self-service agent platforms where teams connect their own MCP servers including Netrows

Netrows MCP Tools for Google ADK (12)

These 12 tools become available when you connect Netrows to Google ADK via MCP:

01

get_account_usage

The Netrows API operates on a credit-based system where each API call consumes 1 credit. Essential for monitoring API consumption, budget management, rate limit awareness, and planning integration usage patterns. AI agents should query this when users ask "how many credits do I have left", "what is my API usage this month", or need to monitor their API consumption before running large batch queries. Check your API account usage and remaining credits

02

get_aircraft_info

g., "N12345" for US-registered, "G-EUUU" for UK). Returns aircraft type (manufacturer and model), registration country, owner/operator information, registration status, year built, engine type (jet, turboprop, piston), number of engines, aircraft age, and category (airline, business jet, private, cargo). Critical for aviation enthusiasts, fleet tracking, aircraft utilization analysis, and private aviation monitoring. AI agents should reference this when users ask "tell me about aircraft N12345", "who owns this tail number", or need aircraft specifications to contextualize flight data. Get registration details and specifications for a specific aircraft

03

get_airline_flights

g., "UA" for United, "DL" for Delta, "BA" for British Airways). Returns flight numbers, aircraft registrations and types, origin-destination pairs, scheduled and actual times, and current status for all flights in the airline fleet. Essential for airline operations monitoring, fleet utilization analysis, competitor intelligence, and passenger rebooking during disruptions. AI agents use this when users ask "show me all United flights right now", "what is Delta flying", or need to track an entire airline operational picture in real-time. List all active flights operated by a specific airline

04

get_airline_info

Returns airline name, IATA/ICAO codes, callsign, country of registration, fleet size, destination count, hub airports, and operational status. Essential for airline industry research, competitor analysis, travel planning context, and aviation market intelligence. AI agents should reference this when users ask "tell me about United Airlines", "what is the ICAO code for Delta", or need airline metadata to contextualize flight and fleet data. Get information and details for a specific airline

05

get_airport_flights

Returns a comprehensive list of inbound and outbound flights with airline/operator, flight number, aircraft type, origin/destination airports, scheduled and actual times, and current flight status (en-route, landed, scheduled, delayed, cancelled, diverted). Essential for airport operations management, passenger pickup coordination, ground handling planning, and flight activity monitoring. AI agents should reference this when users ask "what flights are at X airport", "show me all activity at Y", or need to monitor airport traffic patterns. List all arriving and departing flights at a specific airport

06

get_airport_info

g., "JFK" or "KJFK" for New York JFK, "LAX" or "KLAX" for Los Angeles International). Returns airport name, location (city, state, country), IATA/ICAO/FAA codes, geographic coordinates (latitude, longitude, elevation), timezone, and operational status. Essential for airport identification, travel planning, flight briefing preparation, and geographic reference. AI agents should use this when users ask "tell me about airport X", "what is the ICAO code for Y", or need airport metadata to contextualize flight queries. Get static information and details for a specific airport

07

get_flight_details

Returns departure and arrival airports with full metadata (IATA/ICAO codes, terminal, gate), scheduled and actual times for departure and arrival, aircraft registration and type, airline/operator details, current flight status, and tracking coordinates if airborne. Critical for passenger travel updates, airline operations coordination, and flight tracking dashboards. AI agents should reference this when users request detailed status for a known flight, including gate assignments, timing comparisons, and aircraft information. Get complete details for a specific flight

08

get_flight_schedule

Returns all scheduled flights with airline/operator, flight numbers, aircraft types, departure and arrival times, frequency of service, and days of operation. Essential for route planning, travel itinerary preparation, schedule analysis, and aviation market research. AI agents should reference this when users ask "what flights fly from JFK to LAX", "show me the schedule between ORD and DFW", or need to plan travel between specific airport pairs with comprehensive scheduling options. Get scheduled flights between two airports

09

search_aircraft

Returns all registered aircraft in the operator fleet with registration numbers, aircraft types (manufacturer and model), ages, and current operational status. Essential for fleet analysis, aviation industry research, competitor intelligence, and operator profile generation. AI agents use this when users ask "show me all United Airlines aircraft", "what planes does Delta operate", or need to analyze fleet composition for a specific aviation operator. Search for all aircraft operated by a specific airline or company

10

search_airports

Returns all airports (major international, regional, and general aviation) associated with the queried city including IATA/ICAO codes, full names, locations, distances from city center, and airport types. Essential for travel planning, multi-airport city analysis, alternate airport identification, and geographic aviation research. AI agents use this when users ask "what airports serve Chicago", "find airports in London", or need to identify all airports in a metropolitan area for comprehensive flight searches. Search for airports by city name or location

11

search_flights

The query can be a flight number (e.g., "UAL123"), callsign, or origin-destination airport pair. Returns complete flight identification, airline/operator, aircraft type, departure and arrival airports with IATA/ICAO codes, scheduled and actual times, current position coordinates (latitude, longitude), altitude in feet, ground speed in knots, heading, and flight status (en-route, landed, diverted, cancelled). Essential for real-time flight tracking, passenger pickup coordination, logistics planning, and aviation operations monitoring. AI agents should use this when users ask "where is flight X", "what flights are flying from A to B", or need to track specific flights by number or route. Search for active and recent flights by flight number, callsign, or route

12

track_flight

Returns timestamped position data that can be used to visualize flight progress on maps, estimate arrival times, and monitor flight trajectory. Essential for live flight tracking applications, passenger monitoring, operations dashboards, and aviation enthusiast displays. AI agents use this when users ask "track this flight live", "where is this aircraft right now", or need continuous position updates for an airborne flight. Track real-time position and status of a specific flight

Example Prompts for Netrows in Google ADK

Ready-to-use prompts you can give your Google ADK agent to start working with Netrows immediately.

01

"Search for all active United Airlines flights from Newark to San Francisco."

02

"Show me all airports that serve the city of London and their current flight activity."

03

"Tell me about aircraft N12345 — who owns it, what type is it, and what flights has it been operating?"

Troubleshooting Netrows MCP Server with Google ADK

Common issues when connecting Netrows to Google ADK through the Vinkius, and how to resolve them.

01

McpToolset not found

Update: pip install --upgrade google-adk

Netrows + Google ADK FAQ

Common questions about integrating Netrows MCP Server with Google ADK.

01

How does Google ADK connect to MCP servers?

Import the MCP toolset class and pass the server URL. ADK discovers and registers all tools automatically, making them available to your agent's tool-use loop.
02

Can ADK agents use multiple MCP servers?

Yes. Declare multiple MCP tool providers in your agent configuration. ADK merges all tool schemas and the agent can call tools from any server in a single turn.
03

Which Gemini models work best with MCP tools?

Gemini 2.0 Flash and Pro models both support function calling required for MCP tools. Flash is recommended for latency-sensitive use cases, Pro for complex reasoning.

Connect Netrows to Google ADK

Get your token, paste the configuration, and start using 12 tools in under 2 minutes. No API key management needed.