FareHarbor MCP Server for LlamaIndex 11 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add FareHarbor as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
ASK AI ABOUT THIS MCP SERVER
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 FareHarbor. "
"You have 11 tools available."
),
)
response = await agent.run(
"What tools are available in FareHarbor?"
)
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 FareHarbor MCP Server
Connect your FareHarbor affiliate or partner account to any AI agent and take full control of your tour and activity bookings through natural conversation.
LlamaIndex agents combine FareHarbor tool responses with indexed documents for comprehensive, grounded answers. Connect 11 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
- Operator Discovery — List all authorized tour companies and operators in your network
- Live Inventory Access — Query specific tours (items) and check real-time availability for any date or range
- Seamless Booking — Create new bookings with customer details and ticket types directly from the cloud
- Availability Inspection — Fetch granular details for specific time slots including pricing and remaining capacity
- Booking Management — List recent bookings and retrieve detailed status by UUID flawlessy
- User Context — Verify your API application and user identity credentials through the agent
The FareHarbor MCP Server exposes 11 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 FareHarbor to LlamaIndex via MCP
Follow these steps to integrate the FareHarbor 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 11 tools from FareHarbor
Why Use LlamaIndex with the FareHarbor MCP Server
LlamaIndex provides unique advantages when paired with FareHarbor through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine FareHarbor tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain FareHarbor tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query FareHarbor, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what FareHarbor tools were called, what data was returned, and how it influenced the final answer
FareHarbor + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the FareHarbor MCP Server delivers measurable value.
Hybrid search: combine FareHarbor real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query FareHarbor 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 FareHarbor for fresh data
Analytical workflows: chain FareHarbor queries with LlamaIndex's data connectors to build multi-source analytical reports
FareHarbor MCP Tools for LlamaIndex (11)
These 11 tools become available when you connect FareHarbor to LlamaIndex via MCP:
create_booking
Create a new booking for a tour or activity
get_availability
Get details for a specific availability slot
get_booking
Get details for a specific booking by UUID
get_item_details
Get details for a specific tour or activity
get_me
Get current API user/affiliate identity
list_availabilities_by_date
List available slots for an item on a specific date
list_availabilities_by_range
List available slots for an item within a date range
list_bookings
List recent bookings for a company
list_companies
List all companies (operators) authorized for booking
list_items
List all tours or activities (items) for a specific company
list_lodgings
List lodging/pickup locations for a company
Example Prompts for FareHarbor in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with FareHarbor immediately.
"List the tour companies I can book for."
"Check availability for the Whale Watching tour tomorrow."
"Show me the details for booking UUID abc-123."
Troubleshooting FareHarbor MCP Server with LlamaIndex
Common issues when connecting FareHarbor to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpFareHarbor + LlamaIndex FAQ
Common questions about integrating FareHarbor 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 FareHarbor 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 FareHarbor to LlamaIndex
Get your token, paste the configuration, and start using 11 tools in under 2 minutes. No API key management needed.