How to Use the Beds24 MCP in LlamaIndex

Q: Does the LlamaIndex integration support real-time calendar updates?

Yes, the agent calls getcalendar dynamically during the query pipeline. This guarantees your search results reflect the absolute latest booking status on the platform.

Index your Beds24 booking data directly into LlamaIndex to build a searchable hospitality knowledge base.

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Connect Beds24 MCP to LlamaIndex

Create your Vinkius account to connect Beds24 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 Beds24 with LlamaIndex

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Ground Agent Responses in Live Availability Data

Stop guessing which rooms are open. This MCP Server lets your agent query `get_availability` and `get_calendar` to get real-time occupancy data directly from the source. LlamaIndex indexes these live outputs so your RAG application can answer guest inquiries accurately. Your agent queries the current calendar state, ensuring it never drafts emails for already booked rooms.

Build Searchable Archives of Your Bookings

Turn your historical booking data into a queryable vector store. By pulling records with `list_bookings` and `get_booking`, you feed actual reservation histories into your index. This lets your system answer complex questions about past guest stays or reservation trends. Instead of writing database queries, you search the indexed documents with natural language.

Map Properties with the LlamaIndex MCP Server

Retrieve your entire real estate structure using `list_properties`, `list_rooms`, and `get_property`. The server exposes these endpoints so your agent can build a clear picture of your active rooms. Once indexed, this property data acts as the ground truth for your assistant. When a user asks about specific amenities or room configurations, the agent retrieves the exact property details instantly.

Setup guide

Set up Beds24 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 Beds24 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 Beds24 tools.",
)
response = await agent.run("List recent Beds24 data")

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Beds24. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

Why Choose Vinkius

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Common questions about Beds24 MCP in LlamaIndex

Use the basic MCP client to connect to the server, then convert the tools using the tool spec class. Your agent can run `list_bookings` and index the output documents directly.

Yes, you can use the allowed tools filter during initialization. This lets you restrict your agent to harmless tools like `get_availability` while keeping administrative tools locked down.

Yes, the agent calls `get_calendar` dynamically during the query pipeline. This guarantees your search results reflect the absolute latest booking status on the platform.

It runs over Streamable HTTP, which is fully supported by the framework's MCP tool adapter. This ensures fast, reliable communication between your agent and the API.

We run every connection inside a zero-trust V8 isolate sandbox. Your account tokens are processed ephemerally, ensuring your private property and pricing data is never logged or exposed.

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