How to integrate Chmeetings MCP with LangChain

This guide walks you through connecting Chmeetings to LangChain using the Composio tool router. By the end, you'll have a working Chmeetings agent that can list upcoming church events this month, add new member to youth group, record a donation from a churchgoer through natural language commands. This guide will help you understand how to give your LangChain agent real control over a Chmeetings account through Composio's Chmeetings MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

Chmeetings logoChmeetings
Api Key

Chmeetings is a church management platform for events, members, donations, and volunteers. It streamlines church operations and improves community engagement.

28 Tools

Introduction

This guide walks you through connecting Chmeetings to LangChain using the Composio tool router. By the end, you'll have a working Chmeetings agent that can list upcoming church events this month, add new member to youth group, record a donation from a churchgoer through natural language commands.

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

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

Also integrate Chmeetings with

TL;DR

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

The Chmeetings MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Chmeetings account. It provides structured and secure access to your church management system, so your agent can help you manage events, engage members, track donations, coordinate volunteers, and oversee groups on your behalf.

  • Event planning and scheduling: Empower your agent to create, update, and manage church events, including setting dates, venues, and attendee lists.
  • Member engagement and communication: Let your agent access member directories, send announcements, and track participation to boost overall community involvement.
  • Donation management and reporting: Easily have your agent track contributions, generate donation reports, and assist with financial record-keeping.
  • Volunteer coordination: Allow your agent to organize volunteer opportunities, assign roles, and monitor participation for various church activities.
  • Group and ministry oversight: Ask your agent to manage groups or ministries, enroll members, and keep information up-to-date for effective administration.

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 Chmeetings 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 Chmeetings 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: ['chmeetings']
    }
);

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

Configure the agent with the MCP URL

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

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

Invite Meeting Attendee

Tool to invite a new attendee to a specified meeting.

Get Attendee Details

Tool to retrieve details for a specific attendee.

ChMeetings: Create Meeting

Tool to create a new meeting in ChMeetings.

ChMeetings: Create Organization

Tool to create a new organization.

ChMeetings: Create Reminder

Tool to create/schedule a reminder for a meeting in ChMeetings.

Delete Meeting Attendee

Tool to remove an attendee from a meeting.

List Meeting Attendees

Tool to list attendees of a meeting.

ChMeetings: Delete Meeting

Tool to delete an existing meeting.

ChMeetings: Get Meeting

Tool to retrieve a specific meeting's details by ID.

ChMeetings: Update Meeting

Tool to update meeting details.

ChMeetings: Send Notification

Tool to attempt sending a notification.

ChMeetings: Get Organization

Tool to get details of a specific organization.

ChMeetings: Delete Organization

Tool to delete an existing organization.

ChMeetings: List Organizations

Tool to list all organizations.

ChMeetings: Update Organization

Tool to update an organization's information.

ChMeetings: Delete Person

Tool to delete a person record.

ChMeetings: List People

Tool to retrieve list of People records from ChMeetings.

ChMeetings: Update Person

Tool to update an existing person's information in ChMeetings.

ChMeetings: Create Person

Tool to create a new person record in ChMeetings People directory.

ChMeetings: Get Person

Tool to retrieve a specific person's details by ID.

ChMeetings: Delete Reminder

Tool to cancel a scheduled reminder.

ChMeetings: Get Reminder

Tool to retrieve details of a specific reminder.

ChMeetings: List Reminders

Tool to list reminders from ChMeetings.

ChMeetings: Update Reminder

Tool to update an existing reminder.

ChMeetings: Get Settings

Tool to retrieve account configuration settings.

ChMeetings: Update Settings

Tool to update account settings.

Update attendee role

Tool to update the role of an attendee.

ChMeetings: Get User Profile

Tool to retrieve current user's profile information.

FAQ

Frequently asked questions

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

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

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