How to Use the Gordian Software (Airline Ancillaries API) MCP in LlamaIndex

Q: How do I index seat maps from Gordian Software (Airline Ancillaries API) into LlamaIndex?

You call getsearchresultsbyproduct for seats and load the payload into a LlamaIndex document. The framework indexes the physical layout, making seat attributes searchable via semantic queries.

Q: Can a LlamaIndex agent execute purchases using Gordian Software (Airline Ancillaries API)?

Yes, the agent can call fulfilltrip to complete bookings using settlement options. You expose the MCP tools to a FunctionAgent to allow direct execution from chat interfaces.

Q: How does the Gordian Software (Airline Ancillaries API) MCP Server handle asynchronous search updates in LlamaIndex?

The agent initiates the process with startsearch and polls with getsearchresults. Once the data arrives, LlamaIndex updates the local index nodes dynamically.

Q: What is the quickest way to configure this server with LlamaIndex?

Install llama-index-tools-mcp and instantiate BasicMCPClient pointing to your Vinkius URI. Convert the server tools using McpToolSpec and pass them to your agent.

Index live flight ancillary data directly into your LlamaIndex RAG pipelines.

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Connect Gordian Software (Airline Ancillaries API) MCP to LlamaIndex

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Setup Gordian Software (Airline Ancillaries API) with LlamaIndex

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Indexing seat and bag options in LlamaIndex

The `get_search_results` tool extracts raw itinerary and product data to feed directly into your vector index. LlamaIndex parses this structured JSON, transforming flight seating and baggage pricing into queryable document nodes. Users query your index for specific seating preferences, and the system retrieves exact matches from the cached search data. This stops the agent from hallucinating layout options or baggage fees.

LlamaIndex agent actions via MCP Server tools

The `check_basket` tool verifies current pricing and availability before your RAG agent suggests a purchase. The agent coordinates this with `get_basket` to ensure the vector store matches what is actually staged in the airline's system. When the user confirms, the agent triggers `add_to_basket` to lock in the selection. This direct integration ensures your conversational interface stays aligned with the real-time API state.

Maintaining flight state in your index

The `get_trip` tool pulls the latest booking details to update your local vector database. If a flight changes, the agent uses `inform_changed` to update the index so future queries reflect the current itinerary. This keeps your customer support index accurate. When travelers ask about their luggage allowance, the index pulls the actual active state from the API instead of stale cache files.

Setup guide

Set up Gordian Software (Airline Ancillaries API) 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 Gordian Software (Airline Ancillaries API) 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 Gordian Software (Airline Ancillaries API) tools.",
)
response = await agent.run("List recent Gordian Software (Airline Ancillaries API) data")

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Common questions about Gordian Software (Airline Ancillaries API) MCP in LlamaIndex

You call `get_search_results_by_product` for seats and load the payload into a LlamaIndex document. The framework indexes the physical layout, making seat attributes searchable via semantic queries.

Yes, the agent can call `fulfill_trip` to complete bookings using settlement options. You expose the MCP tools to a `FunctionAgent` to allow direct execution from chat interfaces.

The agent initiates the process with `start_search` and polls with `get_search_results`. Once the data arrives, LlamaIndex updates the local index nodes dynamically.

Install `llama-index-tools-mcp` and instantiate `BasicMCPClient` pointing to your Vinkius URI. Convert the server tools using `McpToolSpec` and pass them to your agent.

The server transmits passenger names and reservation locators through zero-trust, ephemeral V8 isolates. No traveler data persists inside the MCP layer, keeping your customer records secure during index updates.

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