Beds24 MCP Server for LlamaIndex 8 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Beds24 as an MCP tool provider through the 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 Beds24. "
"You have 8 tools available."
),
)
response = await agent.run(
"What tools are available in Beds24?"
)
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 Beds24 MCP Server
Connect Beds24 to any AI agent — the ultra-flexible European channel manager.
LlamaIndex agents combine Beds24 tool responses with indexed documents for comprehensive, grounded answers. Connect 8 tools through the 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
- Properties — All your properties with rooms and capacity
- Bookings — Reservations from all channels with guest details
- Calendar — Price, availability, and restrictions by day
- Availability — Real-time open/closed status per room
- Rooms — Room types, capacity, and channel mappings
The Beds24 MCP Server exposes 8 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 Beds24 to LlamaIndex via MCP
Follow these steps to integrate the Beds24 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 8 tools from Beds24
Why Use LlamaIndex with the Beds24 MCP Server
LlamaIndex provides unique advantages when paired with Beds24 through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Beds24 tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Beds24 tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Beds24, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Beds24 tools were called, what data was returned, and how it influenced the final answer
Beds24 + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Beds24 MCP Server delivers measurable value.
Hybrid search: combine Beds24 real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Beds24 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 Beds24 for fresh data
Analytical workflows: chain Beds24 queries with LlamaIndex's data connectors to build multi-source analytical reports
Beds24 MCP Tools for LlamaIndex (8)
These 8 tools become available when you connect Beds24 to LlamaIndex via MCP:
get_account
Get account info
get_availability
Get room availability
get_booking
Get booking details
get_calendar
Get room calendar
get_property
Get property details
list_bookings
List bookings
list_properties
List properties
list_rooms
List rooms for property
Example Prompts for Beds24 in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Beds24 immediately.
"Show me all bookings arriving this week"
"Adjust the price for the Ocean View Room to Euro 150 for next weekend."
"Generate a brief occupancy report for yesterday."
Troubleshooting Beds24 MCP Server with LlamaIndex
Common issues when connecting Beds24 to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpBeds24 + LlamaIndex FAQ
Common questions about integrating Beds24 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 Beds24 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 Beds24 to LlamaIndex
Get your token, paste the configuration, and start using 8 tools in under 2 minutes. No API key management needed.