How to integrate Zoom MCP with CrewAI

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Introduction

This guide walks you through connecting Zoom to CrewAI using the Composio tool router. By the end, you'll have a working Zoom agent that can schedule a zoom meeting for tomorrow, add a registrant to my next webinar, summarize my last recorded meeting, list participants from yesterday's meeting through natural language commands.

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

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

TL;DR

Here's what you'll learn:
  • Get a Composio API key and configure your Zoom connection
  • Set up CrewAI with an MCP enabled agent
  • Create a Tool Router session or standalone MCP server for Zoom
  • Build a conversational loop where your agent can execute Zoom operations

What is CrewAI?

CrewAI is a powerful framework for building multi-agent AI systems. It provides primitives for defining agents with specific roles, creating tasks, and orchestrating workflows through crews.

Key features include:

  • Agent Roles: Define specialized agents with specific goals and backstories
  • Task Management: Create tasks with clear descriptions and expected outputs
  • Crew Orchestration: Combine agents and tasks into collaborative workflows
  • MCP Integration: Connect to external tools through Model Context Protocol

What is the Zoom MCP server, and what's possible with it?

The Zoom 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 account. It provides structured and secure access to your meetings, webinars, and usage data, so your agent can schedule meetings, register attendees, retrieve recordings, summarize sessions, and analyze participant engagement on your behalf.

  • Automated meeting scheduling and management: Instruct your agent to create new Zoom meetings, fetch details for upcoming or past meetings, and manage all your session logistics effortlessly.
  • Seamless participant and registrant registration: Have your agent add attendees or registrants to meetings and webinars, handling all required information and permissions automatically.
  • On-demand access to recordings and summaries: Let your agent retrieve meeting recordings or generate AI-powered meeting summaries, making it easy to review or share past sessions.
  • Insightful participant analytics: Ask your agent to fetch detailed lists of past meeting participants or generate daily usage reports, helping you track engagement and attendance trends.
  • Efficient recording and data cleanup: Direct your agent to delete outdated recordings or manage your Zoom storage, keeping your account streamlined and organized.

Supported Tools & Triggers

Tools
Add a meeting registrantThis text guides on creating and customizing a user's registration for a zoom meeting, with a max of 4,999 registrants.
Add a webinar registrantZoom users with a webinar plan can create and manage webinars, broadcasting to up to 10,000 attendees.
Create a meetingEnable zoom meeting creation via user-level apps with "me".
Delete meeting recordingsSummary: to delete all meeting recordings, ensure the user's account has cloud recording enabled.
Get a meetingThe text provides details on api permissions for reading meeting information, categorizing permissions into general and granular scopes, and labels the rate limit as 'light'.
Get a meeting summaryMeeting summary info requires a pro+ host plan, ai companion enabled, excluding e2ee meetings.
Get a webinarAccess zoom webinar details requires pro or higher plan and webinar add-on.
Get daily usage reportThe daily report provides zoom service usage details, like new users, meetings, participants, and minutes per day for a month, requiring a pro plan or higher.
Get meeting recordingsTo download meeting recordings, use `download url`.
Get past meeting participantsApi allows paid users (pro+) to fetch past meeting attendee info, excluding solo participants.
List all recordingsThis text details how to list zoom cloud recordings for a user, notably by using "me" for user-level apps and requiring an oauth token for access.
List archived filesZoom's archiving solution enables administrators to automatically record and archive meeting data to third-party platforms for compliance, needing the meeting and webinar archiving feature enabled.
List devicesThis api lets you list devices.
List meetingsThis zoom api lists a user's scheduled meetings using the `me` value for user-level apps, excluding instant meetings and only showing unexpired ones.
List webinar participantsGet a list of past webinar participants with a pro plan or above plus an add-on.
List webinarsThe api lists all scheduled webinars for zoom users with a webinar plan, using `me` for user-level apps.
Update a meetingTo update a meeting via api, ensure `start time` is future-dated; `recurrence` is needed.

What is the Composio tool router, and how does it fit here?

What is Tool Router?

Composio's Tool Router 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 Tool Router

The tool router generates a secure MCP URL that your agents can access to perform actions.

How the Tool Router works

The Tool Router 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

Prerequisites

Before starting, make sure you have:
  • Python 3.9 or higher
  • A Composio account and API key
  • A Zoom connection authorized in Composio
  • An OpenAI API key for the CrewAI LLM
  • Basic familiarity with Python

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.

Install dependencies

bash
pip install composio crewai crewai-tools python-dotenv
What's happening:
  • composio connects your agent to Zoom via MCP
  • crewai provides Agent, Task, Crew, and LLM primitives
  • crewai-tools includes MCP helpers
  • python-dotenv loads environment variables from .env

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_here

Create a .env file in your project root.

What's happening:

  • COMPOSIO_API_KEY authenticates with Composio
  • USER_ID scopes the session to your account
  • OPENAI_API_KEY lets CrewAI use your chosen OpenAI model

Import dependencies

python
from crewai import Agent, Task, Crew, LLM
from crewai_tools import MCPServerAdapter  # optional import if you plan to adapt tools
from composio import Composio
from dotenv import load_dotenv
import os
from crewai.mcp import MCPServerHTTP

load_dotenv()
What's happening:
  • CrewAI classes define agents and tasks, and run the workflow
  • MCPServerHTTP connects the agent to an MCP endpoint
  • Composio will give you a short lived Zoom MCP URL

Create a Composio Tool Router session for Zoom

python
composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
session = composio.create(
    user_id=os.getenv("USER_ID"),
    toolkits=["zoom"],
)
url = session.mcp.url
What's happening:
  • You create a Zoom only session through Composio
  • Composio returns an MCP HTTP URL that exposes Zoom tools

Configure the LLM

python
llm = LLM(
    model="gpt-5-mini",
    api_key=os.getenv("OPENAI_API_KEY"),
)
What's happening:
  • CrewAI will call this LLM for planning and responses
  • You can swap in a different model if needed

Attach the MCP server and create the agent

python
toolkit_agent = Agent(
    role="Zoom Assistant",
    goal="Help users interact with Zoom through natural language commands",
    backstory=(
        "You are an expert assistant with access to Zoom tools. "
        "You can perform various Zoom operations on behalf of the user."
    ),
    mcps=[
        MCPServerHTTP(
            url=url,
            streamable=True,
            cache_tools_list=True,
            headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")},
        ),
    ],
    llm=llm,
    verbose=True,
    max_iter=10,
)
What's happening:
  • MCPServerHTTP connects the agent to the Zoom MCP endpoint
  • cache_tools_list saves a tools catalog for faster subsequent runs
  • verbose helps you see what the agent is doing

Add a REPL loop with Task and Crew

python
print("Chat started! Type 'exit' or 'quit' to end.\n")
print("Try asking the agent to perform Zoom operations.\n")

conversation_context = ""

while True:
    user_input = input("You: ").strip()

    if user_input.lower() in ["exit", "quit", "bye"]:
        print("\nGoodbye!")
        break

    if not user_input:
        continue

    conversation_context += f"\nUser: {user_input}\n"
    print("\nAgent is thinking...\n")

    task = Task(
        description=(
            f"Based on the conversation history:\n{conversation_context}\n\n"
            f"Current user request: {user_input}\n\n"
            f"Please help the user with their Zoom related request."
        ),
        expected_output="A helpful response addressing the user's request",
        agent=toolkit_agent,
    )

    crew = Crew(
        agents=[toolkit_agent],
        tasks=[task],
        verbose=False,
    )

    result = crew.kickoff()
    response = str(result)

    conversation_context += f"Agent: {response}\n"
    print(f"Agent: {response}\n")
What's happening:
  • You build a simple chat loop and keep a running context
  • Each user turn becomes a Task handled by the same agent
  • Crew executes the task and returns a response

Run the application

python
if __name__ == "__main__":
    main()
What's happening:
  • Standard Python entry point so you can run python crewai_zoom_agent.py

Complete Code

Here's the complete code to get you started with Zoom and CrewAI:

python
# file: crewai_zoom_agent.py
from crewai import Agent, Task, Crew, LLM
from crewai_tools import MCPServerAdapter  # optional
from composio import Composio
from dotenv import load_dotenv
import os
from crewai.mcp import MCPServerHTTP

load_dotenv()

def main():
    # Initialize Composio and create a Zoom session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["zoom"],
    )
    url = session.mcp.url

    # Configure LLM
    llm = LLM(
        model="gpt-5-mini",
        api_key=os.getenv("OPENAI_API_KEY"),
    )

    # Create Zoom assistant agent
    toolkit_agent = Agent(
        role="Zoom Assistant",
        goal="Help users interact with Zoom through natural language commands",
        backstory=(
            "You are an expert assistant with access to Zoom tools. "
            "You can perform various Zoom operations on behalf of the user."
        ),
        mcps=[
            MCPServerHTTP(
                url=url,
                streamable=True,
                cache_tools_list=True,
                headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")},
            ),
        ],
        llm=llm,
        verbose=True,
        max_iter=10,
    )

    print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
    print("Try asking the agent to perform Zoom operations.\n")

    conversation_context = ""

    while True:
        user_input = input("You: ").strip()

        if user_input.lower() in ["exit", "quit", "bye"]:
            print("\nGoodbye!")
            break

        if not user_input:
            continue

        conversation_context += f"\nUser: {user_input}\n"
        print("\nAgent is thinking...\n")

        task = Task(
            description=(
                f"Based on the conversation history:\n{conversation_context}\n\n"
                f"Current user request: {user_input}\n\n"
                f"Please help the user with their Zoom related request."
            ),
            expected_output="A helpful response addressing the user's request",
            agent=toolkit_agent,
        )

        crew = Crew(
            agents=[toolkit_agent],
            tasks=[task],
            verbose=False,
        )

        result = crew.kickoff()
        response = str(result)

        conversation_context += f"Agent: {response}\n"
        print(f"Agent: {response}\n")

if __name__ == "__main__":
    main()

Conclusion

You now have a CrewAI agent connected to Zoom through Composio's Tool Router. The agent can perform Zoom operations through natural language commands. Next steps:
  • Add role-specific instructions to customize agent behavior
  • Plug in more toolkits for multi-app workflows
  • Chain tasks for complex multi-step operations

How to build Zoom MCP Agent with another framework

OpenAI Agents SDK

OpenAI Agents SDK

Use Zoom MCP with OpenAI Agents SDK

Claude Agent SDK

Claude Agent SDK

Use Zoom MCP with Claude Agent SDK

Google ADK

Google ADK

Use Zoom MCP with Google ADK

LangChain

LangChain

Use Zoom MCP with LangChain

Vercel AI SDK

Vercel AI SDK

Use Zoom MCP with Vercel AI SDK

Mastra AI

Mastra AI

Use Zoom MCP with Mastra AI

LlamaIndex

LlamaIndex

Use Zoom MCP with LlamaIndex

FAQ

What are the differences in Tool Router MCP and Zoom MCP?

With a standalone Zoom MCP server, the agents and LLMs can only access a fixed set of Zoom tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Zoom and many other apps based on the task at hand, all through a single MCP endpoint.

Can I use Tool Router MCP with CrewAI?

Yes, you can. CrewAI 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 tools.

Can I manage the permissions and scopes for Zoom while using Tool Router?

Yes, absolutely. You can configure which Zoom 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.

How safe is my data with Composio Tool Router?

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 data and credentials are handled as safely as possible.

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