How to integrate Calendarhero MCP with OpenAI Agents SDK

BOOK A CALLGET STARTED FOR FREE
Framework Integration Gradient
Calendarhero Logo
open-ai-agents-sdk Logo
divider

Introduction

This guide walks you through connecting Calendarhero to the OpenAI Agents SDK using the Composio tool router. By the end, you'll have a working Calendarhero agent that can schedule a meeting with my project team, list all meetings i have this week, fetch details for my next scheduled meeting, add a new contact for future meetings through natural language commands.

This guide will help you understand how to give your OpenAI Agents SDK agent real control over a Calendarhero account through Composio's Calendarhero 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 and set up your OpenAI and Composio API keys
  • Install the necessary dependencies
  • Initialize Composio and create a Tool Router session for Calendarhero
  • Configure an AI agent that can use Calendarhero as a tool
  • Run a live chat session where you can ask the agent to perform Calendarhero operations

What is open-ai-agents-sdk?

The OpenAI Agents SDK is a lightweight framework for building AI agents that can use tools and maintain conversation state. It provides a simple interface for creating agents with hosted MCP tool support.

Key features include:

  • Hosted MCP Tools: Connect to external services through hosted MCP endpoints
  • SQLite Sessions: Persist conversation history across interactions
  • Simple API: Clean interface with Agent, Runner, and tool configuration
  • Streaming Support: Real-time response streaming for interactive applications

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

The Calendarhero MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Calendarhero account. It provides structured and secure access to your calendar management tools, so your agent can schedule meetings, manage contacts, fetch meeting details, and access your calendar integrations on your behalf.

  • Automated meeting scheduling and requests: Easily have your agent schedule new meetings, select participants, set time ranges, and include extra meeting details in just a few steps.
  • Contact creation and management: Let the agent create new contacts or fetch existing ones, so scheduling is always quick and accurate.
  • Meeting details retrieval: Ask your agent to fetch specific meeting details or get a list of all meetings within a defined timeframe, keeping you up-to-date.
  • Access and manage calendar integrations: Direct your agent to list all connected calendars, add new integrations, or access available calendars for streamlined scheduling.
  • Template and meeting type discovery: Quickly retrieve available meeting templates and types, letting your agent optimize scheduling based on your preferences and routines.

Supported Tools & Triggers

Tools
Add Calendar ConnectionTool to add a calendar integration to a user's account.
Create ContactTool to create a new contact.
Create Meeting Request V2Tool to create a new meeting request in calendarhero.
Fetch ContactFetch contact
Fetch Meeting DetailsTool to fetch details for meetings within a specified timeframe.
Fetch User ProfileTool to fetch the profile details of the authenticated user.
List MeetingsTool to retrieve the user's meetings within a specified timeframe.
List Meeting TemplatesTool to list all meeting templates available for quick scheduling.
List Meeting TypesTool to retrieve the user's configured meeting types.
List User CalendarsTool to list all calendar integrations connected to a user's calendarhero account.
Search ContactTool to search for existing contacts.
Send ReminderTool to send a reminder to a contact about their scheduled meeting.
Update ContactTool to update details of an existing contact.

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:
  • Composio API Key and OpenAI API Key
  • Primary know-how of OpenAI Agents SDK
  • A live Calendarhero project
  • Some knowledge of Python or Typescript

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

Install dependencies

pip install composio_openai_agents openai-agents python-dotenv

Install the Composio SDK and the OpenAI Agents SDK.

Set up environment variables

bash
OPENAI_API_KEY=sk-...your-api-key
COMPOSIO_API_KEY=your-api-key
USER_ID=composio_user@gmail.com

Create a .env file and add your OpenAI and Composio API keys.

Import dependencies

import asyncio
import os
from dotenv import load_dotenv

from composio import Composio
from composio_openai_agents import OpenAIAgentsProvider
from agents import Agent, Runner, HostedMCPTool, SQLiteSession
What's happening:
  • You're importing all necessary libraries.
  • The Composio and OpenAIAgentsProvider classes are imported to connect your OpenAI agent to Composio tools like Calendarhero.

Set up the Composio instance

load_dotenv()

api_key = os.getenv("COMPOSIO_API_KEY")
user_id = os.getenv("USER_ID")

if not api_key:
    raise RuntimeError("COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key")

# Initialize Composio
composio = Composio(api_key=api_key, provider=OpenAIAgentsProvider())
What's happening:
  • load_dotenv() loads your .env file so OPENAI_API_KEY and COMPOSIO_API_KEY are available as environment variables.
  • Creating a Composio instance using the API Key and OpenAIAgentsProvider class.

Create a Tool Router session

# Create a Calendarhero Tool Router session
session = composio.create(
    user_id=user_id,
    toolkits=["calendarhero"]
)

mcp_url = session.mcp.url

What is happening:

  • You give the Tool Router the user id and the toolkits you want available. Here, it is only calendarhero.
  • The router checks the user's Calendarhero connection and prepares the MCP endpoint.
  • The returned session.mcp.url is the MCP URL that your agent will use to access Calendarhero.
  • This approach keeps things lightweight and lets the agent request Calendarhero tools only when needed during the conversation.

Configure the agent

# Configure agent with MCP tool
agent = Agent(
    name="Assistant",
    model="gpt-5",
    instructions=(
        "You are a helpful assistant that can access Calendarhero. "
        "Help users perform Calendarhero operations through natural language."
    ),
    tools=[
        HostedMCPTool(
            tool_config={
                "type": "mcp",
                "server_label": "tool_router",
                "server_url": mcp_url,
                "headers": {"x-api-key": api_key},
                "require_approval": "never",
            }
        )
    ],
)
What's happening:
  • We're creating an Agent instance with a name, model (gpt-5), and clear instructions about its purpose.
  • The agent's instructions tell it that it can access Calendarhero and help with queries, inserts, updates, authentication, and fetching database information.
  • The tools array includes a HostedMCPTool that connects to the MCP server URL we created earlier.
  • The headers dict includes the Composio API key for secure authentication with the MCP server.
  • require_approval: 'never' means the agent can execute Calendarhero operations without asking for permission each time, making interactions smoother.

Start chat loop and handle conversation

print("\nComposio Tool Router session created.")

chat_session = SQLiteSession("conversation_openai_toolrouter")

print("\nChat started. Type your requests below.")
print("Commands: 'exit', 'quit', or 'q' to end\n")

async def main():
    try:
        result = await Runner.run(
            agent,
            "What can you help me with?",
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")
    except Exception as e:
        print(f"Error: {e}\n")

    while True:
        user_input = input("You: ").strip()
        if user_input.lower() in {"exit", "quit", "q"}:
            print("Goodbye!")
            break

        result = await Runner.run(
            agent,
            user_input,
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")

asyncio.run(main())
What's happening:
  • The program prints a session URL that you visit to authorize Calendarhero.
  • After authorization, the chat begins.
  • Each message you type is processed by the agent using Runner.run().
  • The responses are printed to the console, and conversations are saved locally using SQLite.
  • Typing exit, quit, or q cleanly ends the chat.

Complete Code

Here's the complete code to get you started with Calendarhero and open-ai-agents-sdk:

import asyncio
import os
from dotenv import load_dotenv

from composio import Composio
from composio_openai_agents import OpenAIAgentsProvider
from agents import Agent, Runner, HostedMCPTool, SQLiteSession

load_dotenv()

api_key = os.getenv("COMPOSIO_API_KEY")
user_id = os.getenv("USER_ID")

if not api_key:
    raise RuntimeError("COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key")

# Initialize Composio
composio = Composio(api_key=api_key, provider=OpenAIAgentsProvider())

# Create Tool Router session
session = composio.create(
    user_id=user_id,
    toolkits=["calendarhero"]
)
mcp_url = session.mcp.url

# Configure agent with MCP tool
agent = Agent(
    name="Assistant",
    model="gpt-5",
    instructions=(
        "You are a helpful assistant that can access Calendarhero. "
        "Help users perform Calendarhero operations through natural language."
    ),
    tools=[
        HostedMCPTool(
            tool_config={
                "type": "mcp",
                "server_label": "tool_router",
                "server_url": mcp_url,
                "headers": {"x-api-key": api_key},
                "require_approval": "never",
            }
        )
    ],
)

print("\nComposio Tool Router session created.")

chat_session = SQLiteSession("conversation_openai_toolrouter")

print("\nChat started. Type your requests below.")
print("Commands: 'exit', 'quit', or 'q' to end\n")

async def main():
    try:
        result = await Runner.run(
            agent,
            "What can you help me with?",
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")
    except Exception as e:
        print(f"Error: {e}\n")

    while True:
        user_input = input("You: ").strip()
        if user_input.lower() in {"exit", "quit", "q"}:
            print("Goodbye!")
            break

        result = await Runner.run(
            agent,
            user_input,
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")

asyncio.run(main())

Conclusion

This was a starter code for integrating Calendarhero MCP with OpenAI Agents SDK to build a functional AI agent that can interact with Calendarhero.

Key features:

  • Hosted MCP tool integration through Composio's Tool Router
  • SQLite session persistence for conversation history
  • Simple async chat loop for interactive testing
You can extend this by adding more toolkits, implementing custom business logic, or building a web interface around the agent.

How to build Calendarhero MCP Agent with another framework

Claude Agent SDK

Claude Agent SDK

Use Calendarhero MCP with Claude Agent SDK

Google ADK

Google ADK

Use Calendarhero MCP with Google ADK

LangChain

LangChain

Use Calendarhero MCP with LangChain

Vercel AI SDK

Vercel AI SDK

Use Calendarhero MCP with Vercel AI SDK

Mastra AI

Mastra AI

Use Calendarhero MCP with Mastra AI

LlamaIndex

LlamaIndex

Use Calendarhero MCP with LlamaIndex

CrewAI

CrewAI

Use Calendarhero MCP with CrewAI

FAQ

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

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

Can I use Tool Router MCP with OpenAI Agents SDK?

Yes, you can. OpenAI Agents SDK 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 Calendarhero tools.

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

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

Used by agents from

Context
ASU
Letta
glean
HubSpot
Agent.ai
Altera
DataStax
Entelligence
Rolai
Context
ASU
Letta
glean
HubSpot
Agent.ai
Altera
DataStax
Entelligence
Rolai
Context
ASU
Letta
glean
HubSpot
Agent.ai
Altera
DataStax
Entelligence
Rolai

Never worry about agent reliability

We handle tool reliability, observability, and security so you never have to second-guess an agent action.

Book a callā†—Get started for free