Skyscanner MCP Server for LlamaIndex 6 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Skyscanner as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
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Vinkius supports streamable HTTP and SSE.
import asyncio
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
mcp_client = BasicMCPClient("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
mcp_tool_spec = McpToolSpec(client=mcp_client)
tools = await mcp_tool_spec.to_tool_list_async()
agent = FunctionAgent(
tools=tools,
llm=OpenAI(model="gpt-4o"),
system_prompt=(
"You are an assistant with access to Skyscanner. "
"You have 6 tools available."
),
)
response = await agent.run(
"What tools are available in Skyscanner?"
)
print(response)
asyncio.run(main())
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
About Skyscanner MCP Server
Connect to Skyscanner and explore flight prices worldwide through natural conversation — no API key needed.
LlamaIndex agents combine Skyscanner tool responses with indexed documents for comprehensive, grounded answers. Connect 6 tools through Vinkius and query live data alongside vector stores and SQL databases in a single turn. ideal for hybrid search, data enrichment, and analytical workflows.
What you can do
- Flight Search — Search indicative flight prices between any two airports
- Browse Dates — Find cheapest days to fly around your preferred date
- Browse Grid — Compare prices across multiple date combinations
- Direct Flights — Find non-stop flight options only
- Place Search — Autosuggest airports and cities by name
The Skyscanner MCP Server exposes 6 tools through the Vinkius. Connect it to LlamaIndex in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
How to Connect Skyscanner to LlamaIndex via MCP
Follow these steps to integrate the Skyscanner MCP Server with LlamaIndex.
Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save to agent.py and run: python agent.py
Explore tools
The agent discovers 6 tools from Skyscanner
Why Use LlamaIndex with the Skyscanner MCP Server
LlamaIndex provides unique advantages when paired with Skyscanner through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Skyscanner tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Skyscanner tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Skyscanner, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Skyscanner tools were called, what data was returned, and how it influenced the final answer
Skyscanner + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Skyscanner MCP Server delivers measurable value.
Hybrid search: combine Skyscanner real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Skyscanner to augment indexed data with live information before generating user-facing responses
Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying Skyscanner for fresh data
Analytical workflows: chain Skyscanner queries with LlamaIndex's data connectors to build multi-source analytical reports
Skyscanner MCP Tools for LlamaIndex (6)
These 6 tools become available when you connect Skyscanner to LlamaIndex via MCP:
autosuggest_places
Useful for finding the correct place IDs to use in flight searches. Returns place names, IATA codes and types. Search for places (airports, cities) by name
browse_dates
Useful for finding the cheapest days to fly. Returns prices for multiple dates at once. Browse flight prices by date
browse_grid
Useful for flexible date searches. Returns prices for multiple origin-destination date pairs. Browse flight prices in a date grid
get_geo_places
Useful for discovering available place IDs. Get a list of all supported places
search_direct_flights
Useful for travelers who prefer no layovers. Search for direct flights only
search_flights_indicative
Useful for exploring flight options and comparing prices. Use originPlaceId and destinationPlaceId as IATA codes (e.g. "NYCA" for New York, "LOND" for London) or place IDs. Returns cheapest quotes with carrier info. Search for flight quotes (indicative prices)
Example Prompts for Skyscanner in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Skyscanner immediately.
"Find flights from New York to London on June 15, 2025."
"What's the cheapest day to fly from São Paulo to Miami in July?"
"What's the airport code for Tokyo?"
Troubleshooting Skyscanner MCP Server with LlamaIndex
Common issues when connecting Skyscanner to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpSkyscanner + LlamaIndex FAQ
Common questions about integrating Skyscanner MCP Server with LlamaIndex.
How does LlamaIndex connect to MCP servers?
Can I combine MCP tools with vector stores?
Does LlamaIndex support async MCP calls?
Connect Skyscanner with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Skyscanner to LlamaIndex
Get your token, paste the configuration, and start using 6 tools in under 2 minutes. No API key management needed.