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

Built by Vinkius GDPR 12 Tools Framework

Microsoft AutoGen enables multi-agent conversations where agents negotiate, delegate, and execute tasks collaboratively. Add Netrows as an MCP tool provider through Vinkius and every agent in the group can access live data and take action.

Vinkius supports streamable HTTP and SSE.

python
import asyncio
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.tools.mcp import McpWorkbench

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    async with McpWorkbench(
        server_params={"url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"},
        transport="streamable_http",
    ) as workbench:
        tools = await workbench.list_tools()
        agent = AssistantAgent(
            name="netrows_agent",
            tools=tools,
            system_message=(
                "You help users with Netrows. "
                "12 tools available."
            ),
        )
        print(f"Agent ready with {len(tools)} tools")

asyncio.run(main())
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.

AutoGen enables multi-agent conversations where agents negotiate, delegate, and collaboratively use Netrows tools. Connect 12 tools through Vinkius and assign role-based access. a data analyst queries while a reviewer validates, with optional human-in-the-loop approval for sensitive operations.

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 AutoGen 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 AutoGen via MCP

Follow these steps to integrate the Netrows MCP Server with AutoGen.

01

Install AutoGen

Run pip install "autogen-ext[mcp]"

02

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

03

Integrate into workflow

Use the agent in your AutoGen multi-agent orchestration

04

Explore tools

The workbench discovers 12 tools from Netrows automatically

Why Use AutoGen with the Netrows MCP Server

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

01

Multi-agent conversations: multiple AutoGen agents discuss, delegate, and collaboratively use Netrows tools to solve complex tasks

02

Role-based architecture lets you assign Netrows tool access to specific agents. a data analyst queries while a reviewer validates

03

Human-in-the-loop support: agents can pause for human approval before executing sensitive Netrows tool calls

04

Code execution sandbox: AutoGen agents can write and run code that processes Netrows tool responses in an isolated environment

Netrows + AutoGen Use Cases

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

01

Collaborative analysis: one agent queries Netrows while another validates results and a third generates the final report

02

Automated review pipelines: a researcher agent fetches data from Netrows, a critic agent evaluates quality, and a writer produces the output

03

Interactive planning: agents negotiate task allocation using Netrows data to make informed decisions about resource distribution

04

Code generation with live data: an AutoGen coder agent writes scripts that process Netrows responses in a sandboxed execution environment

Netrows MCP Tools for AutoGen (12)

These 12 tools become available when you connect Netrows to AutoGen 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 AutoGen

Ready-to-use prompts you can give your AutoGen 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 AutoGen

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

01

McpWorkbench not found

Install: pip install "autogen-ext[mcp]"

Netrows + AutoGen FAQ

Common questions about integrating Netrows MCP Server with AutoGen.

01

How does AutoGen connect to MCP servers?

Create an MCP tool adapter and assign it to one or more agents in the group chat. AutoGen agents can then call Netrows tools during their conversation turns.
02

Can different agents have different MCP tool access?

Yes. AutoGen's role-based architecture lets you assign specific MCP tools to specific agents, so a querying agent has different capabilities than a reviewing agent.
03

Does AutoGen support human approval for tool calls?

Yes. Configure human-in-the-loop mode so agents pause and request approval before executing sensitive MCP tool calls.

Connect Netrows to AutoGen

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