How to integrate Apaleo MCP with LangChain

This guide walks you through connecting Apaleo to LangChain using the Composio tool router. By the end, you'll have a working Apaleo agent that can archive a property that's no longer active, clone existing property for new location, create a new unit group for suites through natural language commands. This guide will help you understand how to give your LangChain agent real control over a Apaleo account through Composio's Apaleo MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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Apaleo is a cloud-based property management platform for hospitality businesses. It centralizes reservations, billing, and daily operations for smoother hotel management.

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Introduction

This guide walks you through connecting Apaleo to LangChain using the Composio tool router. By the end, you'll have a working Apaleo agent that can archive a property that's no longer active, clone existing property for new location, create a new unit group for suites through natural language commands.

This guide will help you understand how to give your LangChain agent real control over a Apaleo account through Composio's Apaleo 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
  • Connect your Apaleo project to Composio
  • Create a Tool Router MCP session for Apaleo
  • Initialize an MCP client and retrieve Apaleo tools
  • Build a LangChain agent that can interact with Apaleo
  • Set up an interactive chat interface for testing

What is LangChain?

LangChain is a framework for developing applications powered by language models. It provides tools and abstractions for building agents that can reason, use tools, and maintain conversation context.

Key features include:

  • Agent Framework: Build agents that can use tools and make decisions
  • MCP Integration: Connect to external services through Model Context Protocol adapters
  • Memory Management: Maintain conversation history across interactions
  • Multi-Provider Support: Works with OpenAI, Anthropic, and other LLM providers

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

The Apaleo MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Apaleo account. It provides structured and secure access to your property management operations, so your agent can perform actions like managing properties, handling units, checking availability, and automating setup tasks on your behalf.

  • Property management and archiving: Enable your agent to create, clone, or archive properties, letting you quickly scale or reorganize your portfolio as your business evolves.
  • Unit and unit group operations: Let your agent create new units or unit groups, check if specific units exist, and manage all aspects of your inventory with ease.
  • Attribute and setup automation: Ask your agent to create or verify unit attributes, ensuring your property data is always up-to-date and consistent.
  • Bulk unit creation: Allow your agent to generate multiple units in one go, following custom naming rules, to save you time during onboarding or expansion.
  • Property cloning and rapid deployment: Have your agent clone existing properties with all inventory and rate plans, making it simple to launch new locations based on proven setups.

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 step10 STEPS
1

Prerequisites

Before starting this tutorial, make sure you have:
  • Python 3.10 or higher installed on your system
  • A Composio account with an API key
  • An OpenAI API key
  • Basic familiarity with Python and async programming
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

npm install @composio/langchain @langchain/core @langchain/openai @langchain/mcp-adapters dotenv

Install the required packages for LangChain with MCP support.

What's happening:

  • @composio/langchain provides Composio integration for LangChain
  • @langchain/mcp-adapters enables MCP client connections
  • @langchain/core is the core agent framework
  • dotenv/config loads environment variables
4

Set up environment variables

bash
COMPOSIO_API_KEY=your_composio_api_key_here
COMPOSIO_USER_ID=your_composio_user_id_here
OPENAI_API_KEY=your_openai_api_key_here

Create a .env file in your project root.

What's happening:

  • COMPOSIO_API_KEY authenticates your requests to Composio's API
  • COMPOSIO_USER_ID identifies the user for session management
  • OPENAI_API_KEY enables access to OpenAI's language models
5

Import dependencies

import { Composio } from '@composio/core';
import { LangchainProvider } from '@composio/langchain';
import { MultiServerMCPClient } from "@langchain/mcp-adapters";
import { createAgent } from "langchain";
import * as readline from 'readline';
import 'dotenv/config';

dotenv.config();
What's happening:
  • We're importing LangChain's MCP adapter and Composio SDK
  • The dotenv/config import loads environment variables from your .env file
  • This setup prepares the foundation for connecting LangChain with Apaleo functionality through MCP
6

Initialize Composio client

const composioApiKey = process.env.COMPOSIO_API_KEY;
const userId = process.env.COMPOSIO_USER_ID;

if (!composioApiKey) throw new Error('COMPOSIO_API_KEY is not set');
if (!userId) throw new Error('COMPOSIO_USER_ID is not set');

async function main() {
    const composio = new Composio({
        apiKey: composioApiKey as string,
        provider: new LangchainProvider()
    });
What's happening:
  • We're loading the COMPOSIO_API_KEY from environment variables and validating it exists
  • Creating a Composio instance that will manage our connection to Apaleo tools
  • Validating that COMPOSIO_USER_ID is also set before proceeding
7

Create a Tool Router session

const session = await composio.create(
    userId as string,
    {
        toolkits: ['apaleo']
    }
);

const url = session.mcp.url;
What's happening:
  • We're creating a Tool Router session that gives your agent access to Apaleo tools
  • The create method takes the user ID and specifies which toolkits should be available
  • The returned session.mcp.url is the MCP server URL that your agent will use
  • This approach allows the agent to dynamically load and use Apaleo tools as needed
8

Configure the agent with the MCP URL

const client = new MultiServerMCPClient({
    "apaleo-agent": {
        transport: "http",
        url: url,
        headers: {
            "x-api-key": process.env.COMPOSIO_API_KEY
        }
    }
});

const tools = await client.getTools();

const agent = createAgent({ model: "gpt-5", tools });
What's happening:
  • We're creating a MultiServerMCPClient that connects to our Apaleo MCP server via HTTP
  • The client is configured with a name and the URL from our Tool Router session
  • getTools() retrieves all available Apaleo tools that the agent can use
  • We're creating a LangChain agent using the GPT-5 model
9

Set up interactive chat interface

let conversationHistory: any[] = [];

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

const rl = readline.createInterface({
    input: process.stdin,
    output: process.stdout,
    prompt: 'You: '
});

rl.prompt();

rl.on('line', async (userInput: string) => {
    const trimmedInput = userInput.trim();

    if (['exit', 'quit', 'bye'].includes(trimmedInput.toLowerCase())) {
        console.log("\nGoodbye!");
        rl.close();
        process.exit(0);
    }

    if (!trimmedInput) {
        rl.prompt();
        return;
    }

    conversationHistory.push({ role: "user", content: trimmedInput });
    console.log("\nAgent is thinking...\n");

    const response = await agent.invoke({ messages: conversationHistory });
    conversationHistory = response.messages;

    const finalResponse = response.messages[response.messages.length - 1]?.content;
    console.log(`Agent: ${finalResponse}\n`);
        
        rl.prompt();
    });

    rl.on('close', () => {
        console.log('\n👋 Session ended.');
        process.exit(0);
    });
What's happening:
  • We initialize an empty conversationHistory list to maintain context across interactions
  • A readline interface is used to continuously accept user input from the command line
  • When a user types a message, it's added to the conversation history and sent to the agent
  • The agent processes the request using the invoke() method with the full conversation history
  • Users can type 'exit', 'quit', or 'bye' to end the chat session gracefully
10

Run the application

main().catch((err) => {
    console.error('Fatal error:', err);
    process.exit(1);
});
What's happening:
  • We call the main() function to start the application

Complete Code

Here's the complete code to get you started with Apaleo and LangChain:

import { Composio } from '@composio/core';
import { LangchainProvider } from '@composio/langchain';
import { MultiServerMCPClient } from "@langchain/mcp-adapters";  
import { createAgent } from "langchain";
import * as readline from 'readline';
import 'dotenv/config';

const composioApiKey = process.env.COMPOSIO_API_KEY;
const userId = process.env.COMPOSIO_USER_ID;

if (!composioApiKey) throw new Error('COMPOSIO_API_KEY is not set');
if (!userId) throw new Error('COMPOSIO_USER_ID is not set');

async function main() {
    const composio = new Composio({
        apiKey: composioApiKey as string,
        provider: new LangchainProvider()
    });

    const session = await composio.create(
        userId as string,
        {
            toolkits: ['apaleo']
        }
    );

    const url = session.mcp.url;
    
    const client = new MultiServerMCPClient({
        "apaleo-agent": {
            transport: "http",
            url: url,
            headers: {
                "x-api-key": process.env.COMPOSIO_API_KEY
            }
        }
    });
    
    const tools = await client.getTools();
  
    const agent = createAgent({ model: "gpt-5", tools });
    
    let conversationHistory: any[] = [];
    
    console.log("Chat started! Type 'exit' or 'quit' to end the conversation.\n");
    console.log("Ask any Apaleo related question or task to the agent.\n");
    
    const rl = readline.createInterface({
        input: process.stdin,
        output: process.stdout,
        prompt: 'You: '
    });

    rl.prompt();

    rl.on('line', async (userInput: string) => {
        const trimmedInput = userInput.trim();
        
        if (['exit', 'quit', 'bye'].includes(trimmedInput.toLowerCase())) {
            console.log("\nGoodbye!");
            rl.close();
            process.exit(0);
        }
        
        if (!trimmedInput) {
            rl.prompt();
            return;
        }
        
        conversationHistory.push({ role: "user", content: trimmedInput });
        console.log("\nAgent is thinking...\n");
        
        const response = await agent.invoke({ messages: conversationHistory });
        conversationHistory = response.messages;
        
        const finalResponse = response.messages[response.messages.length - 1]?.content;
        console.log(`Agent: ${finalResponse}\n`);
        
        rl.prompt();
    });

    rl.on('close', () => {
        console.log('\nSession ended.');
        process.exit(0);
    });
}

main().catch((err) => {
    console.error('Fatal error:', err);
    process.exit(1);
});

Conclusion

You've successfully built a LangChain agent that can interact with Apaleo through Composio's Tool Router.

Key features of this implementation:

  • Dynamic tool loading through Composio's Tool Router
  • Conversation history maintenance for context-aware responses
  • Async Python provides clean, efficient execution of agent workflows
You can extend this further by adding error handling, implementing specific business logic, or integrating additional Composio toolkits to create multi-app workflows.
TOOLS

Supported Tools

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

Archive a property

Use this endpoint to archive an existing live property This operation set the IsArchived flag to trueYou must have at least one of these scopes: 'properties.

Check if a property exists

Check if a property exists by id.

Check if a unit attribute exists

Check if a unit attribute existsYou must have at least one of these scopes: 'unitattributes.

Check if a unit exists

Check if a unit exists by id.

Check if a unit group exists

Check if a unit group exists by id.

Clones a property

Use this call to clone a specific property.

Create a unit

Use this call to create a new unit.

Create a unit attribute

Use this call to create a new unit attribute.

Create a unit group

Use this call to create a new unit group.

Create multiple units

Use this call to create multiple units, following a naming rule.

Creates a property

Use this call to create a new property.

Delete a unit

Use this call to delete a unit.

Delete a unit group

Use this call to delete a unit group.

Deletes unit attribute

Deletes unit attributeYou must have at least one of these scopes: 'unitattributes.

Get a properties list

Get the list of properties.

Get a property

Get a property by id.

Get a unit

Get a unit by id.

Get a unit group

Get a unit group by id.

Get a units list

Get the list of units.

Get unit attribute by id

Get unit attribute by idYou must have at least one of these scopes: 'unitattributes.

Get unit attribute list

Get unit attribute listYou must have at least one of these scopes: 'unitattributes.

List Unit Groups

Get the list of unit groups.

Move property to live

Use this endpoint to move an existing test property to live This operation changes the property status to 'Live'You must have at least one of these scopes: 'properties.

Replace a unit group

Use this call to modify a unit group.

Reset Property Data

This endpoint deletes transactional data for a property in 'Test' status.

Returns a list of supported countries

Returns a list of ISO country codes that could be used to create properties.

Returns number of unit groups

Returns number of unit groups matching the filter criteriaYou must have at least one of these scopes: 'unitgroups.

Returns number of units

Returns number of units matching the filter criteriaYou must have at least one of these scopes: 'units.

Return total count of properties

Return total count of propertiesYou need to be authorized (no particular scope required)

FRAMEWORKS

How to build Apaleo MCP Agent with another framework

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Apaleo MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Apaleo MCP with Claude Agent SDK

Claude Code logo

Claude Code

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Claude Cowork logo

Claude Cowork

Use Apaleo MCP with Claude Cowork

Codex logo

Codex

Use Apaleo MCP with Codex

OpenClaw logo

OpenClaw

Use Apaleo MCP with OpenClaw

Hermes logo

Hermes

Use Apaleo MCP with Hermes

CLI logo

CLI

Use Apaleo MCP with CLI

Google ADK logo

Google ADK

Use Apaleo MCP with Google ADK

Vercel AI SDK logo

Vercel AI SDK

Use Apaleo MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Apaleo MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Apaleo MCP with LlamaIndex

CrewAI logo

CrewAI

Use Apaleo MCP with CrewAI

FAQ

Frequently asked questions

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

Yes, you can. LangChain 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 Apaleo tools.

Yes, absolutely. You can configure which Apaleo 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 Apaleo data and credentials are handled as safely as possible.

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