How to Use the Duffel Flights MCP in LlamaIndex

Q: How do I integrate Duffel Flights into a LlamaIndex agent?

Use the McpToolSpec to wrap the server tools. Once registered, pass these tools to your FunctionAgent to enable flight operations.

Q: Can LlamaIndex query flight orders from Duffel Flights?

Yes, use listflightorders to fetch existing bookings. You can then index these results to allow your agent to answer questions about past trips.

Q: Does Duffel Flights work with LlamaIndex async workflows?

The server supports asynchronous tool calls. You can use totoollistasync to ensure your agent doesn't block while waiting for flight data.

Index your flight search results into LlamaIndex knowledge bases to ground your agent in real-time pricing data.

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Connect Duffel Flights MCP to LlamaIndex

Create your Vinkius account to connect Duffel Flights to LlamaIndex 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 Duffel Flights with LlamaIndex

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Index live flight data for better recall

Map the output of `list_flight_offers` directly into your vector store. Your LlamaIndex agents can then query past search results to compare prices or availability without hitting the API again. This approach reduces latency. You get a searchable history of flight data that your agent can reference to provide grounded answers.

Automated order management via agents

Give your agents the power to call `create_flight_order` and `pay_for_flight_order` as part of your RAG pipeline. It allows the agent to book flights based on the context found in your indexed documents. You keep the agent focused on the goal. It finds the right flight in your index and executes the booking through the MCP server tools.

Search airports and airlines semantically

Index the data from `list_airports` and `list_airlines` to let your agents find carriers or hubs using natural language. It removes the need for exact code lookups. Your LlamaIndex agent interprets user intent and maps it to the correct API call. It makes interacting with the Duffel Flights data feel natural.

Setup guide

Set up Duffel Flights MCP in LlamaIndex

Prerequisites

Python 3.10+ installed
llama-index-tools-mcp package
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai. The MCP tools package provides BasicMCPClient and McpToolSpec.
2

Connect with BasicMCPClient
Point BasicMCPClient to your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports SSE and Streamable HTTP transports.
3

Convert to LlamaIndex tools
Call mcp_tool_spec.to_tool_list_async() to convert all Duffel Flights MCP tools into native FunctionTool objects that any LlamaIndex agent can use.
4

Run with any LLM
Create a FunctionAgent with the tools and your preferred LLM. Swap OpenAI for Anthropic, Gemini, or any LlamaIndex-supported provider.

agent.py

from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI

# Connect to the MCP
mcp_client = BasicMCPClient(
    "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)
mcp_tool_spec = McpToolSpec(client=mcp_client)

# Convert MCP tools to LlamaIndex tools
tools = await mcp_tool_spec.to_tool_list_async()

# Create and run the agent
agent = FunctionAgent(
    tools=tools,
    llm=OpenAI(model="gpt-4o"),
    system_prompt="You have access to Duffel Flights tools.",
)
response = await agent.run("List recent Duffel Flights data")

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Common questions about Duffel Flights MCP in LlamaIndex

Use the `McpToolSpec` to wrap the server tools. Once registered, pass these tools to your FunctionAgent to enable flight operations.

Yes, use `list_flight_orders` to fetch existing bookings. You can then index these results to allow your agent to answer questions about past trips.

Tool outputs become text nodes in your index. This allows your agent to perform semantic searches over the flight offers returned by the server.

The server supports asynchronous tool calls. You can use `to_tool_list_async` to ensure your agent doesn't block while waiting for flight data.

The server treats PII as transient input for the booking tools. No passenger names or travel history are stored in your vector index unless you explicitly index them.

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