Netrows MCP Server for Mastra AI 12 tools — connect in under 2 minutes
Mastra AI is a TypeScript-native agent framework built for modern web stacks. Connect Netrows through Vinkius and Mastra agents discover all tools automatically. type-safe, streaming-ready, and deployable anywhere Node.js runs.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import { Agent } from "@mastra/core/agent";
import { createMCPClient } from "@mastra/mcp";
import { openai } from "@ai-sdk/openai";
async function main() {
// Your Vinkius token. get it at cloud.vinkius.com
const mcpClient = await createMCPClient({
servers: {
"netrows": {
url: "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
},
},
});
const tools = await mcpClient.getTools();
const agent = new Agent({
name: "Netrows Agent",
instructions:
"You help users interact with Netrows " +
"using 12 tools.",
model: openai("gpt-4o"),
tools,
});
const result = await agent.generate(
"What can I do with Netrows?"
);
console.log(result.text);
}
main();
* 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.
Mastra's agent abstraction provides a clean separation between LLM logic and Netrows tool infrastructure. Connect 12 tools through Vinkius and use Mastra's built-in workflow engine to chain tool calls with conditional logic, retries, and parallel execution. deployable to any Node.js host in one command.
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 Mastra AI 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 Mastra AI via MCP
Follow these steps to integrate the Netrows MCP Server with Mastra AI.
Install dependencies
Run npm install @mastra/core @mastra/mcp @ai-sdk/openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save to agent.ts and run with npx tsx agent.ts
Explore tools
Mastra discovers 12 tools from Netrows via MCP
Why Use Mastra AI with the Netrows MCP Server
Mastra AI provides unique advantages when paired with Netrows through the Model Context Protocol.
Mastra's agent abstraction provides a clean separation between LLM logic and tool infrastructure. add Netrows without touching business code
Built-in workflow engine chains MCP tool calls with conditional logic, retries, and parallel execution for complex automation
TypeScript-native: full type inference for every Netrows tool response with IDE autocomplete and compile-time checks
One-command deployment to any Node.js host. Vercel, Railway, Fly.io, or your own infrastructure
Netrows + Mastra AI Use Cases
Practical scenarios where Mastra AI combined with the Netrows MCP Server delivers measurable value.
Automated workflows: build multi-step agents that query Netrows, process results, and trigger downstream actions in a typed pipeline
SaaS integrations: embed Netrows as a first-class tool in your product's AI features with Mastra's clean agent API
Background jobs: schedule Mastra agents to query Netrows on a cron and store results in your database automatically
Multi-agent systems: create specialist agents that collaborate using Netrows tools alongside other MCP servers
Netrows MCP Tools for Mastra AI (12)
These 12 tools become available when you connect Netrows to Mastra AI via MCP:
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
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
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
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
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
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
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
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
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
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
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
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 Mastra AI
Ready-to-use prompts you can give your Mastra AI agent to start working with Netrows immediately.
"Search for all active United Airlines flights from Newark to San Francisco."
"Show me all airports that serve the city of London and their current flight activity."
"Tell me about aircraft N12345 — who owns it, what type is it, and what flights has it been operating?"
Troubleshooting Netrows MCP Server with Mastra AI
Common issues when connecting Netrows to Mastra AI through the Vinkius, and how to resolve them.
createMCPClient not exported
npm install @mastra/mcpNetrows + Mastra AI FAQ
Common questions about integrating Netrows MCP Server with Mastra AI.
How does Mastra AI connect to MCP servers?
MCPClient with the server URL and pass it to your agent. Mastra discovers all tools and makes them available with full TypeScript types.Can Mastra agents use tools from multiple servers?
Does Mastra support workflow orchestration?
Connect Netrows with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Netrows to Mastra AI
Get your token, paste the configuration, and start using 12 tools in under 2 minutes. No API key management needed.