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How to integrate Chmeetings MCP with Autogen

Connect Autogen to Chmeetings MCP. List upcoming church events this month, add new member to youth group, and more using natural language, with authentication handled for you.

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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 AutoGen using the Composio tool router. By the end, you'll have a working Chmeetings agent that can create and update meetings, invite attendees, manage people and organizations, set reminders, and send notifications through natural language commands.

This guide will help you understand how to give your AutoGen 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

Claude CodeClaude CoworkOpenAI Agents SDKClaude Agent SDKGrok BotCodexOpenClawHermesAtomic AgentGoogle ADKLangChainVercel AI SDKMastra AILlamaIndexCrewAIPydantic AI

TL;DR

Here's what you'll learn:
  • Get and set up your OpenAI and Composio API keys
  • Install the required dependencies for Autogen and Composio
  • Initialize Composio and create a Tool Router session for Chmeetings
  • Wire that MCP URL into Autogen using McpWorkbench and StreamableHttpServerParams
  • Configure an Autogen AssistantAgent that can call Chmeetings tools
  • Run a live chat loop where you ask the agent to perform Chmeetings operations

What is AutoGen?

Autogen is a framework for building multi-agent conversational AI systems from Microsoft. It enables you to create agents that can collaborate, use tools, and maintain complex workflows.

Key features include:

  • Multi-Agent Systems: Build collaborative agent workflows
  • MCP Workbench: Native support for Model Context Protocol tools
  • Streaming HTTP: Connect to external services through streamable HTTP
  • AssistantAgent: Pre-built agent class for tool-using assistants

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 step08 STEPS
1

Prerequisites

You will need:

  • A Composio API key
  • An OpenAI API key (used by Autogen's OpenAIChatCompletionClient)
  • A Chmeetings account you can connect to Composio
  • Some basic familiarity with Autogen and Python async
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 python-dotenv
pip install autogen-agentchat autogen-ext-openai autogen-ext-tools

Install Composio, Autogen extensions, and dotenv.

What's happening:

  • composio connects your agent to Chmeetings via MCP
  • autogen-agentchat provides the AssistantAgent class
  • autogen-ext-openai provides the OpenAI model client
  • autogen-ext-tools provides MCP workbench support

4

Set up environment variables

bash
COMPOSIO_API_KEY=your-composio-api-key
OPENAI_API_KEY=your-openai-api-key
USER_ID=your-user-identifier@example.com

Create a .env file in your project folder.

What's happening:

  • COMPOSIO_API_KEY is required to talk to Composio
  • OPENAI_API_KEY is used by Autogen's OpenAI client
  • USER_ID is how Composio identifies which user's Chmeetings connections to use
5

Import dependencies and create Tool Router session

python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio

from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient
from autogen_ext.tools.mcp import McpWorkbench, StreamableHttpServerParams

load_dotenv()

async def main():
    # Initialize Composio and create a Chmeetings session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["chmeetings"]
    )
    url = session.mcp.url
What's happening:
  • load_dotenv() reads your .env file
  • Composio(api_key=...) initializes the SDK
  • create(...) creates a Tool Router session that exposes Chmeetings tools
  • session.mcp.url is the MCP endpoint that Autogen will connect to
6

Configure MCP parameters for Autogen

python
# Configure MCP server parameters for Streamable HTTP
server_params = StreamableHttpServerParams(
    url=url,
    timeout=30.0,
    sse_read_timeout=300.0,
    terminate_on_close=True,
    headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")}
)

Autogen expects parameters describing how to talk to the MCP server. That is what StreamableHttpServerParams is for.

What's happening:

  • url points to the Tool Router MCP endpoint from Composio
  • timeout is the HTTP timeout for requests
  • sse_read_timeout controls how long to wait when streaming responses
  • terminate_on_close=True cleans up the MCP server process when the workbench is closed
7

Create the model client and agent

python
# Create model client
model_client = OpenAIChatCompletionClient(
    model="gpt-5",
    api_key=os.getenv("OPENAI_API_KEY")
)

# Use McpWorkbench as context manager
async with McpWorkbench(server_params) as workbench:
    # Create Chmeetings assistant agent with MCP tools
    agent = AssistantAgent(
        name="chmeetings_assistant",
        description="An AI assistant that helps with Chmeetings operations.",
        model_client=model_client,
        workbench=workbench,
        model_client_stream=True,
        max_tool_iterations=10
    )

What's happening:

  • OpenAIChatCompletionClient wraps the OpenAI model for Autogen
  • McpWorkbench connects the agent to the MCP tools
  • AssistantAgent is configured with the Chmeetings tools from the workbench
8

Run the interactive chat loop

python
print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
print("Ask any Chmeetings related question or task to the agent.\n")

# Conversation loop
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")

    # Run the agent with streaming
    try:
        response_text = ""
        async for message in agent.run_stream(task=user_input):
            if hasattr(message, "content") and message.content:
                response_text = message.content

        # Print the final response
        if response_text:
            print(f"Agent: {response_text}\n")
        else:
            print("Agent: I encountered an issue processing your request.\n")

    except Exception as e:
        print(f"Agent: Sorry, I encountered an error: {str(e)}\n")
What's happening:
  • The script prompts you in a loop with You:
  • Autogen passes your input to the model, which decides which Chmeetings tools to call via MCP
  • agent.run_stream(...) yields streaming messages as the agent thinks and calls tools
  • Typing exit, quit, or bye ends the loop

Complete Code

Here's the complete code to get you started with Chmeetings and AutoGen:

python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio

from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient
from autogen_ext.tools.mcp import McpWorkbench, StreamableHttpServerParams

load_dotenv()

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

    # Configure MCP server parameters for Streamable HTTP
    server_params = StreamableHttpServerParams(
        url=url,
        timeout=30.0,
        sse_read_timeout=300.0,
        terminate_on_close=True,
        headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")}
    )

    # Create model client
    model_client = OpenAIChatCompletionClient(
        model="gpt-5",
        api_key=os.getenv("OPENAI_API_KEY")
    )

    # Use McpWorkbench as context manager
    async with McpWorkbench(server_params) as workbench:
        # Create Chmeetings assistant agent with MCP tools
        agent = AssistantAgent(
            name="chmeetings_assistant",
            description="An AI assistant that helps with Chmeetings operations.",
            model_client=model_client,
            workbench=workbench,
            model_client_stream=True,
            max_tool_iterations=10
        )

        print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
        print("Ask any Chmeetings related question or task to the agent.\n")

        # Conversation loop
        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")

            # Run the agent with streaming
            try:
                response_text = ""
                async for message in agent.run_stream(task=user_input):
                    if hasattr(message, 'content') and message.content:
                        response_text = message.content

                # Print the final response
                if response_text:
                    print(f"Agent: {response_text}\n")
                else:
                    print("Agent: I encountered an issue processing your request.\n")

            except Exception as e:
                print(f"Agent: Sorry, I encountered an error: {str(e)}\n")

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

Conclusion

You now have an Autogen assistant wired into Chmeetings through Composio's Tool Router and MCP. From here you can:
  • Add more toolkits to the toolkits list, for example notion or hubspot
  • Refine the agent description to point it at specific workflows
  • Wrap this script behind a UI, Slack bot, or internal tool
Once the pattern is clear for Chmeetings, you can reuse the same structure for other MCP-enabled apps with minimal code changes.
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

Retrieve an attendee's details by attendee ID.

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

List attendees for a specific meeting, with optional pagination.

ChMeetings: Delete Meeting

Tool to delete an existing meeting.

ChMeetings: Get Meeting

Retrieve a 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

List organizations, optionally filtering by search term and specifying pagination.

ChMeetings: Update Organization

Tool to update an organization's information.

ChMeetings: Delete Person

Tool to delete a person record.

ChMeetings: List People

Retrieve a list of People records from ChMeetings, with optional pagination.

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

List reminder records from ChMeetings with optional pagination.

ChMeetings: Update Reminder

Tool to update an existing reminder.

ChMeetings: Get Settings

Retrieve selected lookup values for genders, social statuses, grade levels, and family roles used when creating or updating people and families.

ChMeetings: Update Settings

Tool to update account settings.

Update attendee role

Update an attendee's role by attendee ID.

ChMeetings: Get User Profile

Tool to retrieve current user's profile information.

FRAMEWORKS

How to build Chmeetings MCP Agent with another framework

Claude Code logo

Claude Code

Use Chmeetings MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Chmeetings MCP with Claude Cowork

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Chmeetings MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Chmeetings MCP with Claude Agent SDK

Grok Bot logo

Grok Bot

Use Chmeetings MCP with Grok Bot

Codex logo

Codex

Use Chmeetings MCP with Codex

OpenClaw logo

OpenClaw

Use Chmeetings MCP with OpenClaw

Hermes logo

Hermes

Use Chmeetings MCP with Hermes

Atomic Agent logo

Atomic Agent

Use Chmeetings MCP with Atomic Agent

Google ADK logo

Google ADK

Use Chmeetings MCP with Google ADK

LangChain logo

LangChain

Use Chmeetings MCP with LangChain

Vercel AI SDK logo

Vercel AI SDK

Use Chmeetings MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Chmeetings MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Chmeetings MCP with LlamaIndex

CrewAI logo

CrewAI

Use Chmeetings MCP with CrewAI

Pydantic AI logo

Pydantic AI

Use Chmeetings MCP with Pydantic AI

FAQ

Frequently asked questions

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