How to integrate Altoviz MCP with LangChain

This guide walks you through connecting Altoviz to LangChain using the Composio tool router. By the end, you'll have a working Altoviz agent that can find customer details by email address, update a client's company information, retrieve current vat rates for invoices through natural language commands. This guide will help you understand how to give your LangChain agent real control over a Altoviz account through Composio's Altoviz MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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Altoviz is a cloud-based billing and invoicing platform for businesses. It streamlines online payments, expense tracking, and customizable invoice management.

67 Tools

Introduction

This guide walks you through connecting Altoviz to LangChain using the Composio tool router. By the end, you'll have a working Altoviz agent that can find customer details by email address, update a client's company information, retrieve current vat rates for invoices through natural language commands.

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

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

Also integrate Altoviz with

OpenAI Agents SDKClaude Agent SDKClaude CodeClaude CoworkCodexOpenClawHermesCLIGoogle ADKVercel AI SDKMastra AILlamaIndexCrewAI

TL;DR

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

The Altoviz MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Altoviz account. It provides structured and secure access to your billing, invoicing, and customer management data, so your agent can manage products, find customers, update records, and retrieve financial information on your behalf.

  • Product management and creation: Instruct your agent to create new products, update details, or delete products from your Altoviz catalog with ease.
  • Customer and contact lookup: Effortlessly find customers or contacts by email, enabling quick access to client details and supporting streamlined communication.
  • Financial classification and VAT management: Let your agent fetch available classifications and VAT rates, ensuring accurate tax handling and financial document setup.
  • Unit retrieval for transactions: Retrieve all available measurement units in your system, supporting precise product and invoice management.
  • Customer information updates: Have your agent modify or update customer records, keeping your business data up-to-date without manual intervention.

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 Altoviz 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 Altoviz 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: ['altoviz']
    }
);

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

Configure the agent with the MCP URL

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

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

Create Contact

Creates a new contact in the Altoviz system.

Create Customer

Creates a new customer in Altoviz.

Create Customer Family

Creates a new customer family in Altoviz for categorizing and organizing customers into groups.

Create Product

Creates a new product in the Altoviz system.

Create Product Family

Tool to create a new product family in Altoviz.

Create Receipt

Creates a new receipt in the Altoviz system to record customer payments.

Create Sale Credit

Creates a new draft credit note (avoir) in Altoviz.

Create Sale Invoice

Creates a new draft sale invoice in Altoviz.

Delete Colleague

Tool to delete a colleague from Altoviz.

Delete Customer

Tool to delete a customer from Altoviz.

Delete Customer Family

Tool to delete a customer family from Altoviz.

Delete Product

This tool allows you to delete an existing product from Altoviz.

Delete Product Family

Tool to delete a product family from Altoviz.

Delete Receipt

Tool to delete a receipt from Altoviz.

Delete Draft Sale Credit

Tool to delete a draft credit from Altoviz.

Delete Sale Invoice

Tool to delete a draft sale invoice from Altoviz.

Delete Sale Quote

Tool to delete a sale quote from Altoviz.

Delete Supplier

Tool to delete a supplier from Altoviz.

Download Purchase Invoice

Tool to download a purchase invoice as a PDF file from Altoviz.

Download Sale Credit PDF

Tool to download a sale credit as a PDF file from Altoviz.

Download Sale Invoice PDF

Tool to download a sale invoice as a PDF file from Altoviz.

Find Contact by Email

This tool allows searching for contacts in Altoviz using an email address.

Find Customer by Email

This tool allows you to find a customer in Altoviz by their email address.

Find Product by Number

Search for a product in Altoviz by its product number/SKU.

Find Product by Number or Internal ID

Tool to find a product in Altoviz by exact product number or internal ID.

Find Receipt by Internal ID

Tool to find receipts in Altoviz by customer internal ID.

Find Sale Credits

Tool to find sale credits in Altoviz.

Find Sale Invoices

Tool to find sale invoices in Altoviz.

Find Sale Quotes

Tool to find sale quotes in Altoviz.

Get Classifications List

This tool retrieves a list of classifications from the Altoviz platform.

Get Colleague by ID

Tool to retrieve a colleague's details from Altoviz by their ID.

Get Contact by ID

Tool to retrieve a contact by its unique ID from Altoviz.

Get Current User

Tool to retrieve the current authenticated user's information from Altoviz.

Get Customer by ID

Tool to retrieve a customer by their ID from Altoviz.

Get Customer by Internal ID

Tool to retrieve a single customer from Altoviz by their internal ID.

Get Customer Contacts

Tool to retrieve all contacts associated with a specific customer in Altoviz.

Get Customer Family

Tool to retrieve a customer family by ID from Altoviz.

Get Product by ID

Tool to retrieve a product by its unique ID in Altoviz.

Get Product Family by ID

Tool to retrieve a specific product family by its ID from Altoviz.

Get Receipt by ID

Tool to retrieve a receipt by its ID from Altoviz.

Get Sale Credit by ID

Tool to retrieve a sale credit by its ID from Altoviz.

Get Sale Invoice by ID

Tool to retrieve a sale invoice by its ID from Altoviz.

Get Settings

Tool to retrieve application settings from Altoviz.

Get Supplier by ID

Tool to retrieve a supplier by their ID from Altoviz.

Get Supplier Contacts

Tool to retrieve all contacts associated with a specific supplier in Altoviz.

Get Units List

This tool retrieves a list of all available units in the Altoviz system.

Get VAT Rates

This tool retrieves a list of all available VAT rates from Altoviz.

List Colleagues

Retrieves a list of colleagues from Altoviz.

List Contacts

Tool to retrieve a list of contacts from Altoviz with optional filtering and pagination.

List Customer Families

Tool to list customer families from Altoviz.

List Customers

Tool to retrieve a paginated list of customers from Altoviz.

List Product Families

Tool to retrieve a list of product families from Altoviz.

List Receipts

Tool to retrieve a list of receipts from Altoviz.

List Sale Credits

Tool to retrieve a list of sale credits from Altoviz.

List Sale Invoices

Tool to retrieve a list of sale invoices from Altoviz.

List Sale Quotes

Tool to retrieve a list of sale quotes from Altoviz.

List Suppliers

Tool to retrieve a paginated list of suppliers from Altoviz.

List Webhooks

Tool to retrieve all configured webhooks from Altoviz.

Register Webhook

Tool to register a new webhook in Altoviz.

Test API Key

Tool to test API key validity and retrieve basic account information.

Unregister Webhook

Tool to unregister a webhook from Altoviz.

Update Colleague Information

Updates an existing colleague's information in Altoviz.

Update Customer Information

Updates an existing customer's information in Altoviz.

Update Receipt

Updates an existing receipt in Altoviz.

Update Sale Credit

Tool to update a draft credit note in Altoviz.

Update Supplier Information

Updates an existing supplier's information in Altoviz.

Upload Purchase Invoice

Tool to upload and create a new purchase invoice from a file (PDF or image format).

FRAMEWORKS

How to build Altoviz MCP Agent with another framework

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Altoviz MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Altoviz MCP with Claude Agent SDK

Claude Code logo

Claude Code

Use Altoviz MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Altoviz MCP with Claude Cowork

Codex logo

Codex

Use Altoviz MCP with Codex

OpenClaw logo

OpenClaw

Use Altoviz MCP with OpenClaw

Hermes logo

Hermes

Use Altoviz MCP with Hermes

CLI logo

CLI

Use Altoviz MCP with CLI

Google ADK logo

Google ADK

Use Altoviz MCP with Google ADK

Vercel AI SDK logo

Vercel AI SDK

Use Altoviz MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Altoviz MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Altoviz MCP with LlamaIndex

CrewAI logo

CrewAI

Use Altoviz MCP with CrewAI

FAQ

Frequently asked questions

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

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

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Karan skipped his own birthday party to fix our critical issue. It was 10pm and he diverted his Waymo to help us instead. This really sets the bar — it shows the commitment you need when users rely on your software.

Harsha Gaddipati
Harsha Gaddipati
Co-founder, Slashy

A lot of students tell us that the moment their connected tools start talking to each other inside Opennote feels almost magical. The agent just knows them, and it's immensely helped keep new users on the platform.

Abhi Arya
Abhi Arya
Co-founder, Opennote

We chose Composio over Pipedream because it delivered depth where it mattered — niche tools and tricky edge cases other platforms simply ignored. That gave us confidence to scale without compromising.

Nirman Dave
Nirman Dave
CEO, Zams

As a solo builder, shipping fast is life or death. The only way I can outcompete incumbents is by outmanoeuvring them. Getting bogged down managing agent auth would have been a death sentence.

Ryan Yu
Ryan Yu
Founder, Extra Thursday

Before Composio, adding tool integrations was slow and resource-intensive. Each one could take weeks of engineering time, and maintaining them meant constantly keeping up with API changes.

Tomisin Jenrola
Tomisin Jenrola
Founder & CEO, SwarmZero

With hands-on help from their founder, we integrated Gmail and Google Drive in just 30 minutes. This level of personal support and commitment is exactly what startups should strive for.

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Jerome Leclanche
Co-Founder, Ingram Technologies