How to integrate Order Desk MCP with LangChain

This guide walks you through connecting Order Desk to LangChain using the Composio tool router. By the end, you'll have a working Order Desk agent that can look up orders, add order items, create shipments, add order notes, and manage your inventory through natural language commands. This guide will help you understand how to give your LangChain agent real control over a Order Desk account through Composio's Order Desk MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

Order Desk logoOrder Desk
Api Key

Order Desk is an order management platform for ecommerce orders, shipments, inventory, and store data. It helps teams centralize fulfillment workflows across multiple ecommerce integrations.

20 Tools

Introduction

This guide walks you through connecting Order Desk to LangChain using the Composio tool router. By the end, you'll have a working Order Desk agent that can look up orders, add order items, create shipments, add order notes, and manage your inventory through natural language commands.

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

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

Also integrate Order Desk with

TL;DR

Here's what you'll learn:
  • Get and set up your OpenAI and Composio API keys
  • Connect your Order Desk project to Composio
  • Create a Tool Router MCP session for Order Desk
  • Initialize an MCP client and retrieve Order Desk tools
  • Build a LangChain agent that can interact with Order Desk
  • 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 Order Desk MCP server, and what's possible with it?

The Order Desk MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Order Desk account. It provides structured and secure access to your orders, shipments, inventory, and store data, so your agent can find orders, manage line items, track shipments, update inventory, and organize orders on your behalf.

  • Order search and review: Have your agent find matching orders and retrieve their addresses, items, shipments, notes, discounts, and other details.
  • Order item management: Let the agent list, add, update, or remove line items from an existing order.
  • Shipment management: Direct your agent to create shipment records, review an order's shipments, update shipment details, or remove incorrect records.
  • Inventory management: Instruct your agent to search, create, review, update, or delete inventory items using details such as SKU, name, location, or update time.
  • Order organization and store context: Have your agent add permanent history notes, move orders into the right folder, and review store settings such as locale, timezone, and folder names.

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 Order Desk 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 Order Desk 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: ['order_desk']
    }
);

const url = session.mcp.url;
What's happening:
  • We're creating a Tool Router session that gives your agent access to Order Desk 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 Order Desk tools as needed
8

Configure the agent with the MCP URL

const client = new MultiServerMCPClient({
    "order_desk-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 Order Desk MCP server via HTTP
  • The client is configured with a name and the URL from our Tool Router session
  • getTools() retrieves all available Order Desk 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 Order Desk 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 Order Desk 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: ['order_desk']
        }
    );

    const url = session.mcp.url;
    
    const client = new MultiServerMCPClient({
        "order_desk-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 Order Desk 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 Order Desk 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 Order Desk action and event your agent gets out of the box.

Add Order History Note

Append a timestamped note permanently to an existing order's history.

Add Order Item

Add one line item to an existing order.

Add Order Items

Add two to 10 line items sequentially to the same order and return a result for every processed item.

Create Inventory Item

Create one inventory item with a unique SKU and return its positive Order Desk ID and complete created representation.

Create Inventory Items

Create two to 10 inventory items sequentially and return each created ID or error.

Create Shipments

Create one or more shipment records across orders in one request and report the success or error returned for every shipment.

Delete Inventory Item

Permanently delete one inventory item by its positive Order Desk ID.

Delete Order Item

Permanently remove one line item from an order.

Delete Shipment

Permanently remove one shipment record from an order.

Get Inventory Item

Get one inventory item by its positive Order Desk ID.

Get Order

Get one order and its addresses, line items, shipments, metadata, notes, and discounts by Order Desk internal ID.

Get Store Metadata

Return safe store identity, locale, timezone, page-size settings, and folder IDs and names without exposing credentials or email configuration.

List Inventory Items

Search inventory items in the connected store by ID, SKU, name, metadata, manufacturer SKU, location, or update time.

List Order Items

Return all line items for one order.

List Orders

Find orders in the connected store using at least one narrowing filter and return one bounded page.

List Order Shipments

Return all shipments recorded for one order.

Move Orders

Move one or more orders to exactly one destination folder selected by positive ID or exact name, with a result for every order.

Update Inventory Items

Safely update selected fields on one or more inventory items while preserving every omitted field.

Update Order Item

Safely update selected fields on one order line item while preserving every omitted field.

Update Shipment

Safely update selected fields on one shipment while preserving every omitted field.

FAQ

Frequently asked questions

With a standalone Order Desk MCP server, the agents and LLMs can only access a fixed set of Order Desk tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Order Desk 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 Order Desk tools.

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

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