How to integrate Zoom Team Chat MCP with Pydantic AI

This guide walks you through connecting Zoom Team Chat to Pydantic AI 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 Pydantic AI 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.

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 Pydantic AI 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 Pydantic AI 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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TL;DR

Here's what you'll learn:
  • How to set up your Composio API key and User ID
  • How to create a Composio Tool Router session for Zoom Team Chat
  • How to attach an MCP Server to a Pydantic AI agent
  • How to stream responses and maintain chat history
  • How to build a simple REPL-style chat interface to test your Zoom Team Chat workflows

What is Pydantic AI?

Pydantic AI is a Python framework for building AI agents with strong typing and validation. It leverages Pydantic's data validation capabilities to create robust, type-safe AI applications.

Key features include:

  • Type Safety: Built on Pydantic for automatic data validation
  • MCP Support: Native support for Model Context Protocol servers
  • Streaming: Built-in support for streaming responses
  • Async First: Designed for async/await patterns

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 step09 STEPS
1

Prerequisites

Before starting, make sure you have:
  • Python 3.9 or higher
  • A Composio account with an active 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

bash
pip install composio pydantic-ai python-dotenv

Install the required libraries.

What's happening:

  • composio connects your agent to external SaaS tools like Zoom Team Chat
  • pydantic-ai lets you create structured AI agents with tool support
  • python-dotenv loads your environment variables securely from a .env file
4

Set up environment variables

bash
COMPOSIO_API_KEY=your_composio_api_key_here
USER_ID=your_user_id_here
OPENAI_API_KEY=your_openai_api_key

Create a .env file in your project root.

What's happening:

  • COMPOSIO_API_KEY authenticates your agent to Composio's API
  • USER_ID associates your session with your account for secure tool access
  • OPENAI_API_KEY to access OpenAI LLMs
5

Import dependencies

python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerStreamableHTTP

load_dotenv()
What's happening:
  • We load environment variables and import required modules
  • Composio manages connections to Zoom Team Chat
  • MCPServerStreamableHTTP connects to the Zoom Team Chat MCP server endpoint
  • Agent from Pydantic AI lets you define and run the AI assistant
6

Create a Tool Router Session

python
async def main():
    api_key = os.getenv("COMPOSIO_API_KEY")
    user_id = os.getenv("USER_ID")
    if not api_key or not user_id:
        raise RuntimeError("Set COMPOSIO_API_KEY and USER_ID in your environment")

    # Create a Composio Tool Router session for Zoom Team Chat
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["zoom_chat"],
    )
    url = session.mcp.url
    if not url:
        raise ValueError("Composio session did not return an 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
7

Initialize the Pydantic AI Agent

python
# Attach the MCP server to a Pydantic AI Agent
zoom_chat_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
agent = Agent(
    "openai:gpt-5",
    toolsets=[zoom_chat_mcp],
    instructions=(
        "You are a Zoom Team Chat assistant. Use Zoom Team Chat tools to help users "
        "with their requests. Ask clarifying questions when needed."
    ),
)
What's happening:
  • The MCP client connects to the Zoom Team Chat endpoint
  • The agent uses GPT-5 to interpret user commands and perform Zoom Team Chat operations
  • The instructions field defines the agent's role and behavior
8

Build the chat interface

python
# Simple REPL with message history
history = []
print("Chat started! Type 'exit' or 'quit' to end.\n")
print("Try asking the agent to help you with Zoom Team Chat.\n")

while True:
    user_input = input("You: ").strip()
    if user_input.lower() in {"exit", "quit", "bye"}:
        print("\nGoodbye!")
        break
    if not user_input:
        continue

    print("\nAgent is thinking...\n", flush=True)

    async with agent.run_stream(user_input, message_history=history) as stream_result:
        collected_text = ""
        async for chunk in stream_result.stream_output():
            text_piece = None
            if isinstance(chunk, str):
                text_piece = chunk
            elif hasattr(chunk, "delta") and isinstance(chunk.delta, str):
                text_piece = chunk.delta
            elif hasattr(chunk, "text"):
                text_piece = chunk.text
            if text_piece:
                collected_text += text_piece
        result = stream_result

    print(f"Agent: {collected_text}\n")
    history = result.all_messages()
What's happening:
  • The agent reads input from the terminal and streams its response
  • Zoom Team Chat API calls happen automatically under the hood
  • The model keeps conversation history to maintain context across turns
9

Run the application

python
if __name__ == "__main__":
    asyncio.run(main())
What's happening:
  • The asyncio loop launches the agent and keeps it running until you exit

Complete Code

Here's the complete code to get you started with Zoom Team Chat and Pydantic AI:

python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerStreamableHTTP

load_dotenv()

async def main():
    api_key = os.getenv("COMPOSIO_API_KEY")
    user_id = os.getenv("USER_ID")
    if not api_key or not user_id:
        raise RuntimeError("Set COMPOSIO_API_KEY and USER_ID in your environment")

    # Create a Composio Tool Router session for Zoom Team Chat
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["zoom_chat"],
    )
    url = session.mcp.url
    if not url:
        raise ValueError("Composio session did not return an MCP URL")

    # Attach the MCP server to a Pydantic AI Agent
    zoom_chat_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
    agent = Agent(
        "openai:gpt-5",
        toolsets=[zoom_chat_mcp],
        instructions=(
            "You are a Zoom Team Chat assistant. Use Zoom Team Chat tools to help users "
            "with their requests. Ask clarifying questions when needed."
        ),
    )

    # Simple REPL with message history
    history = []
    print("Chat started! Type 'exit' or 'quit' to end.\n")
    print("Try asking the agent to help you with Zoom Team Chat.\n")

    while True:
        user_input = input("You: ").strip()
        if user_input.lower() in {"exit", "quit", "bye"}:
            print("\nGoodbye!")
            break
        if not user_input:
            continue

        print("\nAgent is thinking...\n", flush=True)

        async with agent.run_stream(user_input, message_history=history) as stream_result:
            collected_text = ""
            async for chunk in stream_result.stream_output():
                text_piece = None
                if isinstance(chunk, str):
                    text_piece = chunk
                elif hasattr(chunk, "delta") and isinstance(chunk.delta, str):
                    text_piece = chunk.delta
                elif hasattr(chunk, "text"):
                    text_piece = chunk.text
                if text_piece:
                    collected_text += text_piece
            result = stream_result

        print(f"Agent: {collected_text}\n")
        history = result.all_messages()

if __name__ == "__main__":
    asyncio.run(main())

Conclusion

You've built a Pydantic AI agent that can interact with Zoom Team Chat through Composio's Tool Router. With this setup, your agent can perform real Zoom Team Chat actions through natural language. You can extend this further by:
  • Adding other toolkits like Gmail, HubSpot, or Salesforce
  • Building a web-based chat interface around this agent
  • Using multiple MCP endpoints to enable cross-app workflows (for example, Gmail + Zoom Team Chat for workflow automation)
This architecture makes your AI agent "agent-native", able to securely use APIs in a unified, composable way without custom integrations.
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.

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. Pydantic AI 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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