How to integrate Callpage MCP with LangChain

This guide walks you through connecting Callpage to LangChain using the Composio tool router. By the end, you'll have a working Callpage agent that can list all widgets with enabled status, get sms statistics for widget 12345, create a custom voice message for spanish visitors through natural language commands. This guide will help you understand how to give your LangChain agent real control over a Callpage account through Composio's Callpage MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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Callpage is a lead capture platform that lets businesses instantly connect with website visitors via callback. It boosts lead generation and increases your sales conversion rates.

26 Tools

Introduction

This guide walks you through connecting Callpage to LangChain using the Composio tool router. By the end, you'll have a working Callpage agent that can list all widgets with enabled status, get sms statistics for widget 12345, create a custom voice message for spanish visitors through natural language commands.

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

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

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

The Callpage MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Callpage account. It provides structured and secure access to your Callpage lead management tools, so your agent can perform actions like retrieving widgets, managing users, monitoring SMS activity, and customizing voice messages on your behalf.

  • Retrieve and manage widgets: Quickly list all your Callpage widgets, access detailed widget configurations, and monitor widget status statistics to optimize lead capture.
  • View and audit account users: Effortlessly fetch lists of all users and managers, including status summaries, to keep your team structure up to date and compliant.
  • Monitor SMS and messaging activity: Access all SMS messages and gather statistics on SMS usage for specific widgets, helping you track engagement and campaign reach.
  • Create custom voice messages: Enable your agent to generate personalized voice greetings for widgets, tailoring communication for both managers and visitors with ease.
  • API connectivity and health checks: Let your agent verify API connectivity and status, ensuring seamless and reliable integration between Callpage and your workflows.

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 Callpage 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 Callpage 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: ['callpage']
    }
);

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

Configure the agent with the MCP URL

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

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

Add Users to Widget

Tool to add users to a widget as managers.

Create SMS Message

Tool to create custom SMS messages for specific widget events.

Create User

Tool to create a new user with specified name, phone number, email and role.

Delete Manager

Tool to delete a manager from a widget.

Delete User by Id

Tool to delete a user by id.

Get All Managers

Tool to retrieve a list of managers for a specific widget with pagination.

Get All SMS Messages

Tool to retrieve all SMS messages for a widget.

Get All Users

Tool to retrieve a list of all users with pagination.

Get All Voice Messages

Tool to retrieve all voice messages for a widget.

Get All Widgets

Tool to retrieve a list of widgets with pagination.

Get API Root

Tool to get the root API greeting.

Get Calls History

Tool to retrieve calls history with filtering and pagination.

Get Manager

Tool to retrieve a specific manager by user_id and widget_id.

Get Manager Status Statistics

Tool to retrieve statistical data about manager statuses.

Get Widget

Tool to retrieve details of a specific widget by id.

Create Manager

Tool to create a new manager for a widget.

Create Voice Message

Tool to create a custom voice message for a widget.

Create Widget

Tool to create a new widget.

Delete Widget by Id

Tool to delete a widget by id.

Reset SMS

Tool to reset SMS messages to default for a widget.

Reset Voice Messages

Tool to reset voice messages to default for a widget.

Update Manager

Tool to update an existing manager.

Update SMS

Tool to update a custom SMS message for a widget.

Update User

Tool to update an existing user by ID.

Update Widget

Tool to update an existing widget.

Widget Call or Schedule

Tool to initiate or schedule a call via widget.

FRAMEWORKS

How to build Callpage MCP Agent with another framework

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Callpage MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Callpage MCP with Claude Agent SDK

Claude Code logo

Claude Code

Use Callpage MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Callpage MCP with Claude Cowork

Codex logo

Codex

Use Callpage MCP with Codex

OpenClaw logo

OpenClaw

Use Callpage MCP with OpenClaw

Hermes logo

Hermes

Use Callpage MCP with Hermes

CLI logo

CLI

Use Callpage MCP with CLI

Google ADK logo

Google ADK

Use Callpage MCP with Google ADK

Vercel AI SDK logo

Vercel AI SDK

Use Callpage MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Callpage MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Callpage MCP with LlamaIndex

CrewAI logo

CrewAI

Use Callpage MCP with CrewAI

FAQ

Frequently asked questions

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

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

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