How to Use the Amadeus MCP in LangChain

Build multi-step travel logic in LangChain using the Amadeus MCP Server to chain flight, hotel, and activity data into your agents.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect Amadeus MCP to LangChain

Create your Vinkius account to connect Amadeus 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.

GDPR Free for Subscribers

Setup Amadeus with LangChain

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Chain complex travel requests in LangChain

Use `search_flights` and `search_hotels` to build chains that handle bookings from start to finish. Your agents link these outputs to refine search parameters dynamically. LangChain agents decide the sequence of execution. They call `get_cheapest_dates` before checking specific flight availability to save time and reduce unnecessary API calls.

Monitor tool performance with LangSmith

Trace every `search_activities` call through your LangChain pipeline. You get full visibility into latency and token usage for every interaction. Debugging becomes simple when you see the exact input sent to `get_airline_info`. You spot bottlenecks in your reasoning chains before they hit production.

Aggregate multi-source data streams

Combine the Amadeus MCP Server with your existing vector stores in one graph. Your LangChain agent pulls live data from `search_transfers` alongside internal company documents. This setup allows for rich, context-aware responses. Your code manages the flow between local databases and remote travel APIs without manual intervention.

Setup guide

Set up Amadeus 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 Amadeus 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({
    "amadeus-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 Amadeus transactions"
    })
    print(result["messages"][-1].content)

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Amadeus. 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.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect Amadeus now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about Amadeus MCP in LangChain

Install the necessary adapters and initialize the MultiServerMCPClient. Point the client to your endpoint, fetch the tool definitions, and inject them into your agent constructor.

The server remains stateless by default. You must use the client session feature in your LangChain implementation if you need to maintain context across multiple turns.

Yes, the framework allows for multi-server aggregation. You pass a list of tool sets to your agent, letting it choose between Amadeus and other connected services.

Vinkius handles authentication through a single endpoint token. Your LangChain environment never sees your raw credentials, keeping your travel data isolated and secure.

The server processes flight, hotel, and location metadata. All traffic is encrypted in transit and never stored on our servers, ensuring your travel history stays private.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript