How to Use the Apaleo MCP in CrewAI

Q: Can I restrict which Apaleo tools a CrewAI agent can use?

Yes, you can use the MCPServerHTTP class from crewai.mcp along with a toolfilter. This lets you restrict access to sensitive tools like listfolios while allowing access to listrooms.

Deploy a cooperative CrewAI team to manage Apaleo reservations and guest billing.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect Apaleo MCP to CrewAI

Create your Vinkius account to connect Apaleo to CrewAI and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

GDPR Free for Subscribers

Setup Apaleo with CrewAI

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Multi-Agent Front Desk Operations with CrewAI

The `list_reservations` tool provides your front-desk crew with a live feed of arriving guests. Inside CrewAI, a Receptionist Agent monitors this feed while a Billing Agent prepares the guest folios in parallel. This cooperative setup uses shared memory to pass reservation IDs from the receptionist to the billing specialist. The billing agent then invokes `list_folios` to ensure all charges are settled before check-in.

Autonomous Room Readiness Monitoring

The `list_rooms` tool exposes the physical inventory and maintenance state of every room in the hotel. A Housekeeping Coordinator Agent analyzes this list to prioritize cleaning schedules based on incoming arrival times. This MCP Server lets the coordinator agent communicate directly with a Reservation Agent. If a guest arrives early, the crew queries `check_availability` to find an alternative clean room of the same type.

Revenue Management and Rate Audits

The `list_rate_plans` tool extracts pricing structures directly from your Apaleo PMS to your MCP Server. A Revenue Analyst Agent reviews these plans to detect pricing discrepancies or outdated seasonal rates. The analyst agent collaborates with a Property Auditor Agent who runs `list_properties` to compare rates across different locations. Together, they compile an optimization report for your management team without human intervention.

Setup guide

Set up Apaleo MCP in CrewAI

Prerequisites

Python 3.10+ installed
crewai package (pip install crewai)
Active Vinkius subscription with a valid endpoint token

1

Install CrewAI
Run pip install crewai to install the framework. MCP support is built-in via the mcps parameter.
2

Add the MCP URL to your agent
Pass your Vinkius endpoint directly to the mcps list. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. CrewAI handles tool discovery and caching automatically.
3

Kick off your crew
Create a Crew with your agent and tasks. Call crew.kickoff() — the agent will automatically invoke Apaleo tools as needed.

crew.py

from crewai import Agent, Task, Crew

agent = Agent(
    role="Apaleo Analyst",
    goal="Access and analyze Apaleo data via MCP.",
    backstory="Expert analyst with direct Apaleo access.",
    mcps=[
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ],
)

task = Task(
    description="List recent Apaleo transactions",
    agent=agent,
    expected_output="A summary of recent activity",
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

Get your connection token →

Prerequisites

Python 3.10+ installed
crewai + crewai-tools packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install crewai crewai-tools. The MCPServerAdapter handles lifecycle management and tool conversion.
2

Connect with MCPServerAdapter
Use MCPServerAdapter as a context manager with SseServerParameters pointing to your Vinkius endpoint. The adapter automatically manages connection lifecycle.
3

Assign tools and run
Pass the returned mcp_tools to your agent's tools parameter. The adapter converts MCP tools to native BaseTool objects compatible with all CrewAI agents.

crew.py

from crewai import Agent, Task, Crew
from crewai_tools import MCPServerAdapter
from mcp import SseServerParameters

server_params = SseServerParameters(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

with MCPServerAdapter(server_params) as mcp_tools:
    agent = Agent(
        role="Apaleo Analyst",
        goal="Access and analyze Apaleo data via MCP.",
        backstory="Expert analyst with direct Apaleo access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent Apaleo transactions",
        agent=agent,
        expected_output="A summary of recent activity",
    )

    crew = Crew(agents=[agent], tasks=[task])
    result = crew.kickoff()
    print(result)

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Apaleo. 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

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect Apaleo now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about Apaleo MCP in CrewAI

Pass your Vinkius HTTP endpoint URL directly into the agent's `mcps` list parameter. CrewAI automatically discovers the tools and exposes them to the agent during execution.

Yes, you can use the `MCPServerHTTP` class from `crewai.mcp` along with a `tool_filter`. This lets you restrict access to sensitive tools like `list_folios` while allowing access to `list_rooms`.

CrewAI uses sequential or hierarchical execution to pass reservation data between specialized agents. One agent pulls reservation details using `get_reservation`, then passes that context to the next agent in the pipeline.

Yes, multiple agents can query the PMS simultaneously. For example, one agent can fetch room types using `list_room_types` while another checks availability using `check_availability`.

Your guest data remains strictly within your PMS and your local CrewAI runtime environment. This MCP Server runs inside an ephemeral, zero-trust sandbox on Vinkius, ensuring no reservation details are cached or logged.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript