How to Use the Amadeus MCP in CrewAI
Deploy autonomous crews of AI agents to research, plan, and monitor travel using Amadeus data with CrewAI.
Works with every AI agent you already use
…and any MCP-compatible client
Connect Amadeus MCP to CrewAI
Create your Vinkius account to connect Amadeus to CrewAI and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.
Assemble a Travel Research Team
Stop using one agent for everything. With CrewAI, you can build a team. Assign a 'Scout Agent' to find interesting destinations using the `get_flight_inspirations` tool. Once it finds a few options, it passes them to a 'Logistics Agent' that uses `search_flights` and `search_hotels` to check prices and availability. You set this up in CrewAI by passing the MCP server URL and using `tool_filter` to give each agent only the tools it needs. This is role-based specialization. The Scout doesn't need to know how to book a hotel, and the Logistics agent doesn't need to look for inspiration. It's more efficient and easier to manage.
Autonomous End-to-End Trip Planning
Build a crew that plans an entire trip without human intervention. A 'Planner Agent' creates a draft itinerary. A 'Fact-Checker Agent' then verifies details, using `get_airline_info` to confirm baggage policies or `get_flight_status` to check for on-time history. Finally, an 'Itinerary Agent' fills out the schedule by calling `search_activities`. This works because CrewAI manages the process, passing context from one agent to the next through a shared memory. The Amadeus tools provide the ground truth for the whole operation. This MCP server acts as the crew's collective window to the live travel market.
Build a Proactive Monitoring Crew
Your agents' work doesn't have to stop after booking. You can create a 'Monitoring Crew' for trips in progress. One 'Flight Watcher' agent repeatedly calls `get_flight_status`. If it detects a delay or cancellation, it triggers an alert and passes the details to a 'Problem Solver' agent. The 'Problem Solver' immediately gets to work, using `search_flights` to find alternatives and `search_hotels_nearby` to find a room near the airport if needed. This is an autonomous system that spots and solves problems, often before the traveler even knows something is wrong. Your MCP Server provides the real-time data that makes it possible.
Set up Amadeus MCP in CrewAI
Prerequisites
- Python 3.10+ installed
-
crewaipackage (pip install crewai) - Active Vinkius subscription with a valid endpoint token
- 1
Install CrewAI
Run
pip install crewaito install the framework. MCP support is built-in via themcpsparameter. - 2
Add the MCP URL to your agent
Pass your Vinkius endpoint directly to the
mcpslist. Replace[YOUR_TOKEN_HERE]with your token from cloud.vinkius.com. CrewAI handles tool discovery and caching automatically. - 3
Kick off your crew
Create a
Crewwith your agent and tasks. Callcrew.kickoff()— the agent will automatically invoke Amadeus tools as needed.
from crewai import Agent, Task, Crew
agent = Agent(
role="Amadeus Analyst",
goal="Access and analyze Amadeus data via MCP.",
backstory="Expert analyst with direct Amadeus access.",
mcps=[
"https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
],
)
task = Task(
description="List recent Amadeus transactions",
agent=agent,
expected_output="A summary of recent activity",
)
crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result) Prerequisites
- Python 3.10+ installed
-
crewai+crewai-toolspackages - Active Vinkius subscription with a valid endpoint token
- 1
Install dependencies
Run
pip install crewai crewai-tools. TheMCPServerAdapterhandles lifecycle management and tool conversion. - 2
Connect with MCPServerAdapter
Use
MCPServerAdapteras a context manager withSseServerParameterspointing to your Vinkius endpoint. The adapter automatically manages connection lifecycle. - 3
Assign tools and run
Pass the returned
mcp_toolsto your agent'stoolsparameter. The adapter converts MCP tools to nativeBaseToolobjects compatible with all CrewAI agents.
from crewai import Agent, Task, Crew
from crewai_tools import MCPServerAdapter
from mcp import SseServerParameters
server_params = SseServerParameters(
url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)
with MCPServerAdapter(server_params) as mcp_tools:
agent = Agent(
role="Amadeus Analyst",
goal="Access and analyze Amadeus data via MCP.",
backstory="Expert analyst with direct Amadeus access.",
tools=mcp_tools,
)
task = Task(
description="List recent Amadeus transactions",
agent=agent,
expected_output="A summary of recent activity",
)
crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result) 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.
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 CrewAI
Use it with your favorite AI tools
Connect this server to Cursor, Claude, VS Code, and more.
Start using the Amadeus MCP today
We host it, we monitor it, we maintain it. You just paste one token.