How to integrate Billsby MCP with LangChain

This guide walks you through connecting Billsby to LangChain using the Composio tool router. By the end, you'll have a working Billsby agent that can list active subscriptions expiring this month, find overdue invoices by customer, update allowance for enterprise plan through natural language commands. This guide will help you understand how to give your LangChain agent real control over a Billsby account through Composio's Billsby MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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Billsby is a subscription billing platform for managing customers, subscriptions, invoices, products, plans, usage counters, add-ons, and allowances. It helps SaaS and subscription teams automate billing operations without building complex billing logic from scratch.

10 Tools

Introduction

This guide walks you through connecting Billsby to LangChain using the Composio tool router. By the end, you'll have a working Billsby agent that can list active subscriptions expiring this month, find overdue invoices by customer, update allowance for enterprise plan through natural language commands.

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

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

Also integrate Billsby 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 Billsby project to Composio
  • Create a Tool Router MCP session for Billsby
  • Initialize an MCP client and retrieve Billsby tools
  • Build a LangChain agent that can interact with Billsby
  • 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 Billsby MCP server, and what's possible with it?

The Billsby MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Billsby account. It provides structured and secure access to your customers, subscriptions, products, plans, and billing details, so your agent can create and update customers, review subscriptions, browse products and plans, check shipping addresses, and monitor billing information on your behalf.

  • Customer creation and updates: Have your agent create customers without subscriptions or payment cards, then update their contact and billing address details when needed.
  • Customer account lookup: Let the agent retrieve a customer’s billing, contact, payment status, and account details, or find customers by a partial name.
  • Subscription review: Direct your agent to list subscriptions and review their billing schedules, status, customer, product, plan, pricing, trial, and revenue details.
  • Product and plan discovery: Instruct your agent to browse products by name or visibility and review the plans and billing cycles available for each product.
  • Subscription shipping details: Have your agent retrieve the shipping address associated with a subscription when you need to confirm delivery information.

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 Billsby 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 Billsby 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: ['billsby']
    }
);

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

Configure the agent with the MCP URL

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

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

Create Customer

Create a Billsby customer without a subscription or payment card.

Get Customer

Get billing, contact, payment-status, and account details for one Billsby customer.

Get Subscription

Get billing schedule, customer, product, plan, pricing, status, and revenue details for one Billsby subscription.

Get Subscription Shipping Address

Get the shipping address associated with one Billsby subscription.

List Customers

Return one page of customers for the connected Billsby company, optionally filtered by a partial customer name.

List Customer Subscriptions

List all subscriptions belonging to one Billsby customer.

List Product Plans

List the plans and billing cycles configured for one Billsby product.

List Products

Return one page of Billsby products, optionally filtered by name or visibility.

List Subscriptions

Return one page of company subscriptions with optional status, trial, product, plan, and ordering filters.

Update Customer

Replace the editable contact and billing-address details for an existing Billsby customer.

FRAMEWORKS

How to build Billsby MCP Agent with another framework

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Billsby MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Billsby MCP with Claude Agent SDK

Claude Code logo

Claude Code

Use Billsby MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Billsby MCP with Claude Cowork

Codex logo

Codex

Use Billsby MCP with Codex

OpenClaw logo

OpenClaw

Use Billsby MCP with OpenClaw

Hermes logo

Hermes

Use Billsby MCP with Hermes

CLI logo

CLI

Use Billsby MCP with CLI

Google ADK logo

Google ADK

Use Billsby MCP with Google ADK

Vercel AI SDK logo

Vercel AI SDK

Use Billsby MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Billsby MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Billsby MCP with LlamaIndex

CrewAI logo

CrewAI

Use Billsby MCP with CrewAI

FAQ

Frequently asked questions

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

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

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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.

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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.

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