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How to integrate Lodgify MCP with Autogen

Connect Autogen to Lodgify MCP. Show available dates for property 1234, list all airbnb channel reservations this week, and more using natural language, with authentication handled for you.

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Lodgify is an all-in-one vacation rental software for property managers and owners. It centralizes bookings, guest messaging, and channel synchronization in one dashboard.

30 Tools

Introduction

This guide walks you through connecting Lodgify to AutoGen using the Composio tool router. By the end, you'll have a working Lodgify agent that can list properties and reservations, check and set availability, handle enquiries, read messaging threads, and list channel connections through natural language commands.

This guide will help you understand how to give your AutoGen agent real control over a Lodgify account through Composio's Lodgify MCP server.

Before we dive in, let's take a quick look at the key ideas and tools involved.

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TL;DR

Here's what you'll learn:
  • Get and set up your OpenAI and Composio API keys
  • Install the required dependencies for Autogen and Composio
  • Initialize Composio and create a Tool Router session for Lodgify
  • Wire that MCP URL into Autogen using McpWorkbench and StreamableHttpServerParams
  • Configure an Autogen AssistantAgent that can call Lodgify tools
  • Run a live chat loop where you ask the agent to perform Lodgify operations

What is AutoGen?

Autogen is a framework for building multi-agent conversational AI systems from Microsoft. It enables you to create agents that can collaborate, use tools, and maintain complex workflows.

Key features include:

  • Multi-Agent Systems: Build collaborative agent workflows
  • MCP Workbench: Native support for Model Context Protocol tools
  • Streaming HTTP: Connect to external services through streamable HTTP
  • AssistantAgent: Pre-built agent class for tool-using assistants

What is the Lodgify MCP server, and what's possible with it?

The Lodgify MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Lodgify account. It provides structured and secure access to your vacation rental properties, channels, and reservations, so your agent can perform actions like checking property availability, synchronizing channel data, retrieving reservations, and managing listings on your behalf.

  • Property availability checks: Instantly ask your agent to retrieve up-to-date availability information for any property, including pricing, minimum stay requirements, and current bookings.
  • Reservation management across channels: Let your agent list and filter reservations from all your connected channels, making it easy to track bookings and guest details in one place.
  • Channel synchronization and connection insights: Effortlessly pull a list of all channel connections and mappings, ensuring your property data stays in sync across platforms like Airbnb, Booking.com, and more.
  • Property portfolio overview: Quickly retrieve and paginate through all your properties, so you can get a comprehensive view of your listings and manage them at scale.
  • Supported country and channel discovery: Have your agent fetch supported countries and available channels to help with onboarding new properties or expanding your rental business.

What is the Composio tool router, and how does it fit here?

What is Composio SDK?

Composio's Composio SDK helps agents find the right tools for a task at runtime. You can plug in multiple toolkits (like Gmail, HubSpot, and GitHub), and the agent will identify the relevant app and action to complete multi-step workflows. This can reduce token usage and improve the reliability of tool calls. Read more here: Getting started with Composio SDK

The tool router generates a secure MCP URL that your agents can access to perform actions.

How the Composio SDK works

The Composio SDK follows a three-phase workflow:

  1. Discovery: Searches for tools matching your task and returns relevant toolkits with their details.
  2. Authentication: Checks for active connections. If missing, creates an auth config and returns a connection URL via Auth Link.
  3. Execution: Executes the action using the authenticated connection.

Step-by-step Guide

Step by step08 STEPS
1

Prerequisites

You will need:

  • A Composio API key
  • An OpenAI API key (used by Autogen's OpenAIChatCompletionClient)
  • A Lodgify account you can connect to Composio
  • Some basic familiarity with Autogen and Python async
2

Getting API Keys for OpenAI and Composio

OpenAI API Key
  • Go to the OpenAI dashboard and create an API key. You'll need credits to use the models, or you can connect to another model provider.
  • Keep the API key safe.
Composio API Key
  • Log in to the Composio dashboard.
  • Navigate to your API settings and generate a new API key.
  • Store this key securely as you'll need it for authentication.
3

Install dependencies

bash
pip install composio python-dotenv
pip install autogen-agentchat autogen-ext-openai autogen-ext-tools

Install Composio, Autogen extensions, and dotenv.

What's happening:

  • composio connects your agent to Lodgify via MCP
  • autogen-agentchat provides the AssistantAgent class
  • autogen-ext-openai provides the OpenAI model client
  • autogen-ext-tools provides MCP workbench support

4

Set up environment variables

bash
COMPOSIO_API_KEY=your-composio-api-key
OPENAI_API_KEY=your-openai-api-key
USER_ID=your-user-identifier@example.com

Create a .env file in your project folder.

What's happening:

  • COMPOSIO_API_KEY is required to talk to Composio
  • OPENAI_API_KEY is used by Autogen's OpenAI client
  • USER_ID is how Composio identifies which user's Lodgify connections to use
5

Import dependencies and create Tool Router session

python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio

from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient
from autogen_ext.tools.mcp import McpWorkbench, StreamableHttpServerParams

load_dotenv()

async def main():
    # Initialize Composio and create a Lodgify session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["lodgify"]
    )
    url = session.mcp.url
What's happening:
  • load_dotenv() reads your .env file
  • Composio(api_key=...) initializes the SDK
  • create(...) creates a Tool Router session that exposes Lodgify tools
  • session.mcp.url is the MCP endpoint that Autogen will connect to
6

Configure MCP parameters for Autogen

python
# Configure MCP server parameters for Streamable HTTP
server_params = StreamableHttpServerParams(
    url=url,
    timeout=30.0,
    sse_read_timeout=300.0,
    terminate_on_close=True,
    headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")}
)

Autogen expects parameters describing how to talk to the MCP server. That is what StreamableHttpServerParams is for.

What's happening:

  • url points to the Tool Router MCP endpoint from Composio
  • timeout is the HTTP timeout for requests
  • sse_read_timeout controls how long to wait when streaming responses
  • terminate_on_close=True cleans up the MCP server process when the workbench is closed
7

Create the model client and agent

python
# Create model client
model_client = OpenAIChatCompletionClient(
    model="gpt-5",
    api_key=os.getenv("OPENAI_API_KEY")
)

# Use McpWorkbench as context manager
async with McpWorkbench(server_params) as workbench:
    # Create Lodgify assistant agent with MCP tools
    agent = AssistantAgent(
        name="lodgify_assistant",
        description="An AI assistant that helps with Lodgify operations.",
        model_client=model_client,
        workbench=workbench,
        model_client_stream=True,
        max_tool_iterations=10
    )

What's happening:

  • OpenAIChatCompletionClient wraps the OpenAI model for Autogen
  • McpWorkbench connects the agent to the MCP tools
  • AssistantAgent is configured with the Lodgify tools from the workbench
8

Run the interactive chat loop

python
print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
print("Ask any Lodgify related question or task to the agent.\n")

# Conversation loop
while True:
    user_input = input("You: ").strip()

    if user_input.lower() in ["exit", "quit", "bye"]:
        print("\nGoodbye!")
        break

    if not user_input:
        continue

    print("\nAgent is thinking...\n")

    # Run the agent with streaming
    try:
        response_text = ""
        async for message in agent.run_stream(task=user_input):
            if hasattr(message, "content") and message.content:
                response_text = message.content

        # Print the final response
        if response_text:
            print(f"Agent: {response_text}\n")
        else:
            print("Agent: I encountered an issue processing your request.\n")

    except Exception as e:
        print(f"Agent: Sorry, I encountered an error: {str(e)}\n")
What's happening:
  • The script prompts you in a loop with You:
  • Autogen passes your input to the model, which decides which Lodgify tools to call via MCP
  • agent.run_stream(...) yields streaming messages as the agent thinks and calls tools
  • Typing exit, quit, or bye ends the loop

Complete Code

Here's the complete code to get you started with Lodgify and AutoGen:

python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio

from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient
from autogen_ext.tools.mcp import McpWorkbench, StreamableHttpServerParams

load_dotenv()

async def main():
    # Initialize Composio and create a Lodgify session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["lodgify"]
    )
    url = session.mcp.url

    # Configure MCP server parameters for Streamable HTTP
    server_params = StreamableHttpServerParams(
        url=url,
        timeout=30.0,
        sse_read_timeout=300.0,
        terminate_on_close=True,
        headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")}
    )

    # Create model client
    model_client = OpenAIChatCompletionClient(
        model="gpt-5",
        api_key=os.getenv("OPENAI_API_KEY")
    )

    # Use McpWorkbench as context manager
    async with McpWorkbench(server_params) as workbench:
        # Create Lodgify assistant agent with MCP tools
        agent = AssistantAgent(
            name="lodgify_assistant",
            description="An AI assistant that helps with Lodgify operations.",
            model_client=model_client,
            workbench=workbench,
            model_client_stream=True,
            max_tool_iterations=10
        )

        print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
        print("Ask any Lodgify related question or task to the agent.\n")

        # Conversation loop
        while True:
            user_input = input("You: ").strip()

            if user_input.lower() in ['exit', 'quit', 'bye']:
                print("\nGoodbye!")
                break

            if not user_input:
                continue

            print("\nAgent is thinking...\n")

            # Run the agent with streaming
            try:
                response_text = ""
                async for message in agent.run_stream(task=user_input):
                    if hasattr(message, 'content') and message.content:
                        response_text = message.content

                # Print the final response
                if response_text:
                    print(f"Agent: {response_text}\n")
                else:
                    print("Agent: I encountered an issue processing your request.\n")

            except Exception as e:
                print(f"Agent: Sorry, I encountered an error: {str(e)}\n")

if __name__ == "__main__":
    asyncio.run(main())

Conclusion

You now have an Autogen assistant wired into Lodgify through Composio's Tool Router and MCP. From here you can:
  • Add more toolkits to the toolkits list, for example notion or hubspot
  • Refine the agent description to point it at specific workflows
  • Wrap this script behind a UI, Slack bot, or internal tool
Once the pattern is clear for Lodgify, you can reuse the same structure for other MCP-enabled apps with minimal code changes.
TOOLS

Supported Tools

Every Lodgify action and event your agent gets out of the box.

Create Call Me Back Request

Creates a Call Me Back request for a guest concerning a property inquiry or booking.

Create Enquiry

Tool to create a new general enquiry with guest and reservation details.

Decline Enquiry

Tool to decline an enquiry, changing its status to Declined.

Delete Enquiry

Tool to delete an enquiry by moving it to the trash.

Delete Reservations

Moves multiple bookings or enquiries to the trash in a single batch operation.

Get Countries

Tool to retrieve all available countries.

Get Country by Code

Tool to retrieve a specific country by its ISO code.

Get Currency By Code

Tool to retrieve currency details by its code.

Get Deleted Properties

Retrieves deleted property IDs, optionally filtered by deletion datetime.

Get External Bookings

Tool to retrieve external bookings for a specific booking ID.

Get Messaging Thread

Tool to retrieve details of a messaging thread.

Get Property Availability

Retrieves availability information for a specific property within a date range.

Get Room Type Availability

Retrieves availability calendar data for a specific room type within a property for a given date range.

Get Unread Count

Retrieves the total count of unread bookings and enquiries.

Get V1 Availability

Retrieves availability information for all properties and room types associated with the authenticated account over a specified date range.

List Channel Connections

Lists channel connections, with optional pagination and status or channel filters.

List Channel Mappings

Lists channel mappings, optionally filtered by property, channel code, or external ID, with pagination.

List Channel Reservations

Lists channel reservations with property, channel, creation-date, limit and offset parameters; a single request may not return all results.

List Channels

Lists available distribution channels in the Lodgify account, including their IDs, names, descriptions, and active status.

List Currencies

Tool to retrieve all available currency codes.

List Properties

Retrieves a paginated list of Lodgify properties, including IDs, names, and addresses when available.

List Reservations

Tool to retrieve a paginated list of bookings and enquiries from the inbox.

List Webhooks

Lists webhook configurations for the Lodgify account, including IDs, event types, and target URLs when available.

Mark Reservations Not Replied

Tool to batch mark bookings and enquiries as not replied.

Mark Reservations Replied

Tool to batch mark bookings or enquiries as replied.

Recover Enquiry

Tool to restore an enquiry that was previously moved to the trash.

Reopen Enquiry

Tool to reopen an enquiry, changing its status to Open.

Set Availability

Updates the number of available units for a specific room type within a date range.

Subscribe to Webhook

Subscribes to a Lodgify webhook by providing a target URL and event type.

Unsubscribe Webhook

Tool to unsubscribe from a Lodgify webhook.

FRAMEWORKS

How to build Lodgify MCP Agent with another framework

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Claude Agent SDK

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Grok Bot logo

Grok Bot

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Codex logo

Codex

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OpenClaw logo

OpenClaw

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Hermes logo

Hermes

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Atomic Agent logo

Atomic Agent

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Google ADK logo

Google ADK

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LangChain logo

LangChain

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Vercel AI SDK logo

Vercel AI SDK

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Mastra AI logo

Mastra AI

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LlamaIndex logo

LlamaIndex

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CrewAI logo

CrewAI

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Pydantic AI logo

Pydantic AI

Use Lodgify MCP with Pydantic AI

FAQ

Frequently asked questions

With a standalone Lodgify MCP server, the agents and LLMs can only access a fixed set of Lodgify tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Lodgify and many other apps based on the task at hand, all through a single MCP endpoint.

Yes, you can. Autogen fully supports MCP integration. You get structured tool calling, message history handling, and model orchestration while Tool Router takes care of discovering and serving the right Lodgify tools.

Yes, absolutely. You can configure which Lodgify scopes and actions are allowed when connecting your account to Composio. You can also bring your own OAuth credentials or API configuration so you keep full control over what the agent can do.

All sensitive data such as tokens, keys, and configuration is fully encrypted at rest and in transit. Composio is SOC 2 Type 2 compliant and follows strict security practices so your Lodgify data and credentials are handled as safely as possible.

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