How to integrate Zoom Team Chat MCP with LangChain

This guide walks you through connecting Zoom Team Chat to LangChain using the Composio tool router. By the end, you'll have a working Zoom Team Chat agent that can create channels, manage shared spaces, add space members, bookmark messages, and set reminders through natural language commands. This guide will help you understand how to give your LangChain agent real control over a Zoom Team Chat account through Composio's Zoom Team Chat MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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Zoom Team Chat logoZoom Team Chat
Oauth2

Zoom Team Chat is Zoom's persistent messaging service for channels, direct messages, threads, reactions, files, reminders, and shared spaces. It keeps team conversations organized and searchable inside the Zoom workspace.

44 Tools

Introduction

This guide walks you through connecting Zoom Team Chat to LangChain using the Composio tool router. By the end, you'll have a working Zoom Team Chat agent that can create channels, manage shared spaces, add space members, bookmark messages, and set reminders through natural language commands.

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

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

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

The Zoom Team Chat MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Zoom Team Chat account. It provides structured and secure access to your messages, channels, contacts, reminders, and shared spaces, so your agent can send messages, manage channels, organize conversations, set reminders, and coordinate shared spaces on your behalf.

  • Messaging and thread management: Have your agent send messages to channels or contacts, schedule messages, retrieve conversations and threads, and delete messages you no longer need.
  • Channel coordination: Let the agent create, find, join, archive, or delete channels, invite members, and review channel membership.
  • Message organization: Direct your agent to pin, bookmark, react to, or mark messages as read or unread, then review pinned and bookmarked content.
  • Reminders and follow-ups: Instruct your agent to create message reminders, list upcoming reminders, or remove reminders after tasks are complete.
  • Contacts and shared spaces: Have your agent find company contacts, create and manage shared spaces, add or remove members, and organize channels within those spaces.

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 Zoom Team Chat 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 Zoom Team Chat 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: ['zoom_chat']
    }
);

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

Configure the agent with the MCP URL

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

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

Add Shared Space Members

Add members to a Zoom Team Chat shared space by email address or Zoom user ID.

Archive or Unarchive Channels

Archive or unarchive up to 10 Zoom Team Chat channels in one call.

Bookmark or Unbookmark Message

Add or remove a bookmark on a Zoom Team Chat message.

Create Channel

Create a new Zoom Team Chat channel for the authenticated user, optionally inviting initial members by email.

Create Message Reminder

Set a reminder on a Zoom Team Chat message, either after a delay (delay_seconds) or at an absolute time (remind_time).

Create Shared Space

Create a Zoom Team Chat shared space (a container that groups related channels).

Delete Channel

Delete a Zoom Team Chat channel the user owns or is a member of.

Delete Message

Delete a Zoom Team Chat message the connected user sent, identified by message_id plus the conversation it lives in.

Delete Message Reminder

Delete the reminder set on a Zoom Team Chat message.

Delete Scheduled Message

Delete a scheduled (draft) Zoom Team Chat message before it is sent, identified by draft_id plus the conversation it is addressed to.

Delete Shared Space

Delete a Zoom Team Chat shared space.

Get Channel

Get full information about a Zoom Team Chat channel, including its settings.

Get Chat Contact

Get a single Zoom Team Chat contact by email or user ID, optionally with live presence status.

Get Message

Get a single Zoom Team Chat message by ID, including its deep-link URL.

Get Message Thread

Retrieve a Zoom Team Chat message's thread: the parent message plus its replies since a given time.

Get Shared Space

Get details of a Zoom Team Chat shared space, including its owner and settings.

Invite Channel Members

Invite members to a Zoom Team Chat channel by email address.

Join Channel

Join a public Zoom Team Chat channel as the authenticated user.

Leave Channel

Leave a Zoom Team Chat channel.

List Bookmarks

List the authenticated user's bookmarked Zoom Team Chat messages, optionally filtered to one channel (to_channel) or one 1:1 contact (to_contact).

List Channel Members

List the members of a Zoom Team Chat channel.

List Channels

List the Zoom Team Chat channels the authenticated user is a member of.

List Chat Contacts

List the authenticated user's Zoom Team Chat contacts.

List Messages

List Zoom Team Chat messages exchanged in a channel or a 1:1 conversation, newest first (defaults to today).

List Pinned Messages

List the pinned messages of a Zoom Team Chat channel.

List Reminders

List the authenticated user's Zoom Team Chat message reminders.

List Scheduled Messages

List the user's scheduled (draft) Zoom Team Chat messages queued to send to a channel or a 1:1 contact.

List Chat Sessions

List the user's recent Zoom Team Chat sessions (channels and 1:1 conversations) within a time window.

List Shared Space Channels

List the channels grouped inside a Zoom Team Chat shared space.

List Shared Space Members

List the members and administrators of a Zoom Team Chat shared space.

List Shared Spaces

List the Zoom Team Chat shared spaces the authenticated user belongs to.

Mark Message Read or Unread

Mark a Zoom Team Chat message as read or unread.

Move Channels Into/Out of Shared Space

Move existing Zoom Team Chat channels into or out of a shared space.

Pin or Unpin Message

Pin or unpin a message in a Zoom Team Chat channel.

React to Message

Add or remove an emoji reaction on a Zoom Team Chat message.

Remove Channel Member

Remove a single member from a Zoom Team Chat channel.

Remove Shared Space Members

Remove members or administrators from a Zoom Team Chat shared space by user ID or member ID (the shared space owner cannot be removed).

Search Channels

Search Zoom Team Chat channels by name — fuzzy keywords or an exact channel name — across the channels the user has joined or the org's public channels.

Search Company Contacts

Search the connected user's organization directory for contacts by keyword (first name, last name, or email address).

Send Message

Send a Zoom Team Chat message to a channel or a 1:1 contact, optionally as a thread reply (reply_main_message_id) or scheduled for later (scheduled_time).

Star or Unstar Conversation

Star or unstar a Zoom Team Chat channel or contact for the authenticated user.

Update Channel

Rename a Zoom Team Chat channel or update its type/settings.

Update Message

Edit the text of an existing Zoom Team Chat message.

Update Shared Space

Update a Zoom Team Chat shared space's name, description, or settings.

FRAMEWORKS

How to build Zoom Team Chat MCP Agent with another framework

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Zoom Team Chat MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Zoom Team Chat MCP with Claude Agent SDK

Claude Code logo

Claude Code

Use Zoom Team Chat MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Zoom Team Chat MCP with Claude Cowork

Codex logo

Codex

Use Zoom Team Chat MCP with Codex

OpenClaw logo

OpenClaw

Use Zoom Team Chat MCP with OpenClaw

Hermes logo

Hermes

Use Zoom Team Chat MCP with Hermes

CLI logo

CLI

Use Zoom Team Chat MCP with CLI

Google ADK logo

Google ADK

Use Zoom Team Chat MCP with Google ADK

Vercel AI SDK logo

Vercel AI SDK

Use Zoom Team Chat MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Zoom Team Chat MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Zoom Team Chat MCP with LlamaIndex

CrewAI logo

CrewAI

Use Zoom Team Chat MCP with CrewAI

FAQ

Frequently asked questions

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

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

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