How to Use the United Airlines MCP in LangChain

Q: How do I use United Airlines with LangChain to find historical delays?

You call the getflighthistory tool, specifying a past date and the desired type (arrival or departure). The resulting delay data can then be passed into another chain step to calculate an average on-time performance score for that route.

Q: Can United Airlines schedule changes be handled using LangChain?

Yes. You start by calling getflightbynumber to establish the typical route and then use getfutureflights with a future date. If you need more context, you can follow up by checking getairlineinfo to confirm carrier details.

Q: If I'm building an automation system for United Airlines using LangChain, how do I handle real-time data?

For immediate status checks, you use the getflightstatus tool. This provides current gate, terminal, and estimated times instantly. You can then integrate this live data into a larger agent workflow that informs the user immediately.

Q: What specific data type does this United Airlines MCP Server touch regarding flight status?

The server tracks operational flight statuses, including 'scheduled', 'active', 'landed', 'cancelled', and 'delayed'. These values are returned by tools like getflightstatus.

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Connect United Airlines MCP to LangChain

Create your Vinkius account to connect United Airlines to LangChain 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 United Airlines with LangChain

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Perplexity

United Airlines MCP Server for complex workflows

You can chain tool calls to answer deeply nested questions. For instance, you first check if United flies between two cities using `get_route`, then use the resulting IATA codes to fetch detailed airport information with `get_airport_info`. This sequence of actions tells your agent exactly what's going on.

Multi-step flight status tracking

Need to know why a flight is delayed? Use the MCP Server to first check historical performance via `get_flight_history`. Then, you can use the current date and airport codes in combination with `get_arrivals` or `get_departures` to pinpoint the specific operational impact. It builds a complete picture of service disruption.

Fleet analysis and route verification

This MCP Server lets you build agents that verify entire networks. An agent can fetch static fleet details with `get_aircraft_fleet`, cross-reference those types against the operational routes from `get_airline_routes`, and check if specific airports have landing capabilities using `get_airport_info`. It's perfect for pre-launch planning.

Setup guide

Set up United Airlines MCP in LangChain

Prerequisites

Python 3.10+ installed
langchain-mcp-adapters + langgraph packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install langchain-mcp-adapters langgraph langchain-openai. The MCP adapters package converts MCP tools into native LangChain BaseTool objects.
2

Connect via HTTP transport
Use MultiServerMCPClient with "transport": "http" pointing to your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Create a ReAct agent
Pass the discovered tools to create_react_agent() from LangGraph. The agent automatically routes United Airlines tool calls through the MCP protocol.
4

Run with any LLM
Swap ChatOpenAI for ChatAnthropic, ChatGoogleGenerativeAI, or any LangChain-compatible model. The MCP tools work identically across all providers.

agent.py

from langchain_mcp_adapters.client import MultiServerMCPClient
from langgraph.prebuilt import create_react_agent
from langchain_openai import ChatOpenAI

async with MultiServerMCPClient({
    "united-airlines-mcp": {
        "transport": "http",
        "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
    }
}) as client:
    tools = client.get_tools()

    agent = create_react_agent(
        ChatOpenAI(model="gpt-4o"),
        tools,
    )
    result = await agent.ainvoke({
        "messages": "List recent United Airlines transactions"
    })
    print(result["messages"][-1].content)

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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 United Airlines. 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 United Airlines MCP in LangChain

You call the `get_flight_history` tool, specifying a past date and the desired type (arrival or departure). The resulting delay data can then be passed into another chain step to calculate an average on-time performance score for that route.

Yes. You start by calling `get_flight_by_number` to establish the typical route and then use `get_future_flights` with a future date. If you need more context, you can follow up by checking `get_airline_info` to confirm carrier details.

For immediate status checks, you use the `get_flight_status` tool. This provides current gate, terminal, and estimated times instantly. You can then integrate this live data into a larger agent workflow that informs the user immediately.

The MCP Server gives detailed information including the full name, city, country, and geographic coordinates using `get_airport_info`. This data is useful for validating codes or building location-based services.

The server tracks operational **flight statuses**, including 'scheduled', 'active', 'landed', 'cancelled', and 'delayed'. These values are returned by tools like `get_flight_status`.

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