How to Use the Amadeus MCP in AutoGen

Create debating travel agents in AutoGen using the Amadeus MCP Server to reach consensus on your next trip.

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Connect Amadeus MCP to AutoGen

Create your Vinkius account to connect Amadeus to AutoGen 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 Amadeus with AutoGen

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Perplexity

Debate flight options in AutoGen

Assign one agent to check `get_cheapest_dates` and another to verify `get_flight_status`. They discuss these findings until they agree on the best itinerary. This multi-agent approach prevents bias. One agent focuses on budget while the other prioritizes reliability, forcing a balanced final recommendation.

Negotiate travel plans between agents

Your AutoGen agents use `search_hotels_nearby` to challenge each other's location preferences. They negotiate until the chosen hotel meets all defined criteria. This process mimics human deliberation. You get a result that accounts for multiple constraints, such as price, proximity, and availability, simultaneously.

Automate complex queries with Amadeus

Use `search_transfers` and `search_activities` to fill in the gaps of a travel itinerary. The McpToolAdapter handles the schema so your agents talk to the server effortlessly. Agents orchestrate these calls without you writing glue code. They fetch data, share it within the conversation, and refine the plan based on the feedback they give each other.

Setup guide

Set up Amadeus MCP in AutoGen

Prerequisites

Python 3.10+ installed
autogen-ext[mcp] package
Active Vinkius subscription with a valid endpoint token

1

Install AutoGen with MCP
Run pip install "autogen-ext[mcp]" autogen-agentchat. The MCP extension includes mcp_server_tools for stateless tool access.
2

Fetch tools from the MCP
Call mcp_server_tools(SseServerParams(url=...)) with your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Run your agent
Pass the tools to AssistantAgent and call agent.run(). The agent invokes Amadeus tools and returns structured results.

agent.py

from autogen_ext.tools.mcp import SseServerParams, mcp_server_tools
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

server_params = SseServerParams(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

tools = await mcp_server_tools(server_params)

agent = AssistantAgent(
    name="Amadeus_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent Amadeus data")
print(result.messages[-1].content)

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Prerequisites

Python 3.10+ installed
autogen-ext[mcp] + autogen-agentchat
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Same packages as above. McpWorkbench is ideal when your agent needs stateful sessions across multiple tool calls.
2

Use McpWorkbench as context manager
Wrap your agent in async with McpWorkbench(...) to maintain shared state and resources. The workbench manages the full MCP session lifecycle.
3

Run with workbench
Pass workbench=workbench to your agent. State is preserved across multiple tool calls within the same session.

agent.py

from autogen_ext.tools.mcp import McpWorkbench, SseServerParams
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

server_params = SseServerParams(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

async with McpWorkbench(server_params) as workbench:
    agent = AssistantAgent(
        name="Amadeus_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent Amadeus data")
    print(result.messages[-1].content)

Get your connection token →

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Common questions about Amadeus MCP in AutoGen

Use the McpToolAdapter to register the server tools. Pass the resulting list into your AssistantAgent constructor to give your agents access to the API.

Yes, they can challenge results if they do not meet the specified constraints. This is the primary strength of the debate-driven architecture in this framework.

The server supports both stdio and HTTP transports. You choose the one that fits your deployment architecture during the initialization phase.

Your endpoint token acts as the only key. Vinkius manages the secure gateway, ensuring that your agents only access the travel records you authorize.

The server transmits flight schedules, hotel rates, and coordinate data. All these records are handled in memory and discarded immediately after the agent conversation concludes.

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