How to integrate OneTapCheckIn MCP with Autogen

This guide walks you through connecting OneTapCheckIn to AutoGen using the Composio tool router. By the end, you'll have a working OneTapCheckIn agent that can create attendee lists, add participants, find profiles, review alerts, and manage your profiles through natural language commands. This guide will help you understand how to give your AutoGen agent real control over a OneTapCheckIn account through Composio's OneTapCheckIn MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

OneTapCheckIn logoOneTapCheckIn
Api Key

OneTapCheckIn is an event attendance platform for managing attendees, profiles, check-ins, passports, integrations, and alerts. It helps teams run smoother events with faster check-ins and clearer attendance tracking.

19 Tools

Introduction

This guide walks you through connecting OneTapCheckIn to AutoGen using the Composio tool router. By the end, you'll have a working OneTapCheckIn agent that can create attendee lists, add participants, find profiles, review alerts, and manage your profiles through natural language commands.

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

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

Also integrate OneTapCheckIn with

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 OneTapCheckIn
  • Wire that MCP URL into Autogen using McpWorkbench and StreamableHttpServerParams
  • Configure an Autogen AssistantAgent that can call OneTapCheckIn tools
  • Run a live chat loop where you ask the agent to perform OneTapCheckIn 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 OneTapCheckIn MCP server, and what's possible with it?

The OneTapCheckIn MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your OneTapCheckIn account. It provides structured and secure access to your events, attendee profiles, attendance records, passports, alerts, and organization settings, so your agent can create event lists, manage attendee profiles, add participants, track attendance, and review event information on your behalf.

  • Event list management: Have your agent create, find, update, or delete event and check-in lists for your organization.
  • Attendee profile management: Let the agent create, search, update, or delete attendee profiles, including batches of up to 25 profiles and values based on your configured custom fields.
  • Participant organization: Direct your agent to add existing profiles to lists, find attendance records, update participant details, or remove participants from a list.
  • Attendance tracking: Instruct your agent to check in, check out, undo check-ins, or undo checkouts for one participant or batches of up to 25 participants.
  • Passports, alerts, and organization details: Have your agent review attendee passports, attendance alerts, automation rules, check-in confirmation settings, and connected organization information.

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 OneTapCheckIn 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 OneTapCheckIn 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 OneTapCheckIn 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 OneTapCheckIn session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["onetapcheckin"]
    )
    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 OneTapCheckIn 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 OneTapCheckIn assistant agent with MCP tools
    agent = AssistantAgent(
        name="onetapcheckin_assistant",
        description="An AI assistant that helps with OneTapCheckIn 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 OneTapCheckIn 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 OneTapCheckIn 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 OneTapCheckIn 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 OneTapCheckIn 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 OneTapCheckIn session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["onetapcheckin"]
    )
    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 OneTapCheckIn assistant agent with MCP tools
        agent = AssistantAgent(
            name="onetapcheckin_assistant",
            description="An AI assistant that helps with OneTapCheckIn 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 OneTapCheckIn 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 OneTapCheckIn 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 OneTapCheckIn, you can reuse the same structure for other MCP-enabled apps with minimal code changes.
TOOLS

Supported Tools

Every OneTapCheckIn action and event your agent gets out of the box.

Add Participants

Add one or more existing profiles to one or more lists without checking them in.

Create List

Create an event/check-in list.

Create Profile

Create one person profile without adding it to a list.

Create Profiles

Create 1 to 25 person profiles in input order using one provider request per profile.

Delete List

Permanently delete one list by ID.

Delete Profile

Permanently delete one profile.

Find Lists

Get one list by exact ID or search the connected organization's lists.

Find Participants

Get one participant by exact ID or search attendance records by list, profile, status, text, or date range.

Find Profiles

Get one profile by ID or search profiles by identity, list, passport, or check-in code.

Get Organization

Return the organization associated with the connected API key.

Get Profile Custom Fields

Return the organization's configured profile custom-field definitions so an agent can use valid field names and value types when creating or updating profiles.

List Alerts

Return one page of organization alert and automation rules together with outbound check-in confirmation settings.

List Passports

List one page of standard passports for exactly one profile or participant.

Remove Participant

Remove one participant record from its list.

Update List

Partially update a list.

Update Participant

Update metadata on one participant record without performing check-in or checkout.

Update Participant Attendance

Check in, check out, undo check-in, or undo checkout for one known participant.

Update Participant Attendance Batch

Apply one shared check-in, checkout, undo check-in, or undo checkout operation to 1 to 25 participants in input order, using one provider request per item.

Update Profile

Partially update one profile.

FAQ

Frequently asked questions

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

Yes, you can. Autogen 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 OneTapCheckIn tools.

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

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