How to Use the Amenitiz MCP in LlamaIndex

Q: Can LlamaIndex query past Amenitiz reservations without hitting the API?

Yes, you can index the output of listreservations into a local vector database. Your agent then queries this local index first, saving API call overhead and speeding up response times.

Build a searchable knowledge base of your hotel inventory by indexing Amenitiz PMS data into LlamaIndex vector stores.

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Connect Amenitiz MCP to LlamaIndex

Create your Vinkius account to connect Amenitiz 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 Amenitiz with LlamaIndex

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Index live hotel pricing data using this MCP Server

The `get_rates` tool extracts current room prices directly from your property management system via the MCP standard. LlamaIndex reads these rates and indexes them, allowing your agent to answer complex pricing questions without hitting the live API every time. By grounding your agent's responses in this structured data, you eliminate pricing hallucinations. Your agent compares rates across different seasons by querying the local vector index instead of guessing.

Retrieve guest profiles for semantic search

The `list_guests` tool pulls customer history, contact details, and stay preferences into your LlamaIndex document store. This turns flat guest lists into queryable data points that your agent can search semantically. When a returning guest calls, your agent searches the indexed guest profiles to surface past preferences. The agent can instantly adjust the conversation based on historical booking behaviors recorded in your PMS.

Map room availability to customer queries

The `get_availability` tool feeds real-time occupancy data directly into your retrieval-augmented generation pipelines. This ensures your agent only offers rooms that are actually open for booking during the requested dates. Your system uses `list_room_types` to match vague user descriptions like a quiet room with a view to actual room categories. By combining live status with semantic indexing, the agent finds the perfect room without manual filtering.

Setup guide

Set up Amenitiz 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 Amenitiz 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 Amenitiz tools.",
)
response = await agent.run("List recent Amenitiz data")

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Common questions about Amenitiz MCP in LlamaIndex

You initialize the MCP client and convert the tools using the LlamaIndex tool spec helper. From there, your pipeline calls `list_rooms` to fetch room configurations and index them as document nodes.

Yes, you can index the output of `list_reservations` into a local vector database. Your agent then queries this local index first, saving API call overhead and speeding up response times.

For real-time data, your agent bypasses the static vector index and calls `get_availability` directly. This gives you the best of both worlds: fast semantic search for static info and live checks for booking status.

Yes, you can combine this MCP Server with other data source specs in LlamaIndex. This lets your agent query hotel rooms alongside local tourism database indexes in a unified query engine.

All API requests to the PMS go through encrypted HTTPS channels. No reservation records or room rates are cached on Vinkius servers, keeping your guest data isolated inside your private LlamaIndex memory space.

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