How to integrate Cardly MCP with OpenAI Agents SDK

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Introduction

This guide walks you through connecting Cardly to the OpenAI Agents SDK using the Composio tool router. By the end, you'll have a working Cardly agent that can create a new contact list named 'vip clients', list all available artwork for our next campaign, generate a preview of a card using latest artwork, review recent credit history for this account through natural language commands.

This guide will help you understand how to give your OpenAI Agents SDK agent real control over a Cardly account through Composio's Cardly 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 Cardly
  • Configure an AI agent that can use Cardly as a tool
  • Run a live chat session where you can ask the agent to perform Cardly 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 Cardly MCP server, and what's possible with it?

The Cardly MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Cardly account. It provides structured and secure access to your Cardly workspace, so your agent can create contact lists, generate card previews, manage invitations, and access artwork or credit history for seamless customer engagement tasks.

  • Automated contact list creation and management: Easily instruct your agent to set up new contact lists or manage existing ones, streamlining outreach campaigns and personalized mailings.
  • Card preview generation and artwork browsing: Let your agent generate watermarked card previews and browse available artwork to help you select the right designs before sending mailers.
  • Real-time credit and gift history access: Ask your agent to fetch your credit or gift credit history so you always know your account status and can track usage or plan new campaigns.
  • Invitation and webhook management: Direct your agent to handle invitations—listing, deleting, or auditing user invites—or manage webhooks for seamless integration with other systems.
  • Font and design asset exploration: Have your agent list available fonts and artwork, making it easier to choose creative assets for your next customer engagement initiative.

Supported Tools & Triggers

Tools
Create Contact ListTool to add a new contact list.
Create WebhookTool to create a new webhook subscription.
Delete Invitation by EmailTool to delete an invitation by email address.
Delete WebhookTool to delete a webhook.
Generate PreviewTool to generate a low-quality, watermarked preview document for a card.
List ArtworkTool to retrieve the currently available artwork for your organisation.
List Credit HistoryTool to list credit history records.
List FontsTool to list your currently available fonts.
List Gift Credit HistoryTool to list gift credit history records for your organization.
List InvitationsTool to retrieve active invitations for your organisation with optional filters.
List MediaTool to retrieve the currently available media sizes for product artwork.
List OrdersTool to retrieve orders placed by your organisation.
List TemplatesTool to retrieve your currently available templates from cardly.
List UsersTool to retrieve all users associated with your account.
List WebhooksTool to retrieve any active or disabled webhooks set up for your organisation.
List Writing StylesTool to list available writing styles.
Retrieve Account BalanceTool to retrieve the current account and gift credit balances for your organisation.
Retrieve OrderTool to retrieve information on a specific order.
Retrieve UserTool to retrieve detailed information about a specific user.
Update WebhookTool to update a webhook’s settings, including target url and events.

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 Cardly 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 Cardly.

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 Cardly Tool Router session
session = composio.create(
    user_id=user_id,
    toolkits=["cardly"]
)

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 cardly.
  • The router checks the user's Cardly connection and prepares the MCP endpoint.
  • The returned session.mcp.url is the MCP URL that your agent will use to access Cardly.
  • This approach keeps things lightweight and lets the agent request Cardly 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 Cardly. "
        "Help users perform Cardly 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 Cardly 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 Cardly 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 Cardly.
  • 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 Cardly 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=["cardly"]
)
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 Cardly. "
        "Help users perform Cardly 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 Cardly MCP with OpenAI Agents SDK to build a functional AI agent that can interact with Cardly.

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 Cardly MCP Agent with another framework

Claude Agent SDK

Claude Agent SDK

Use Cardly MCP with Claude Agent SDK

Google ADK

Google ADK

Use Cardly MCP with Google ADK

LangChain

LangChain

Use Cardly MCP with LangChain

Vercel AI SDK

Vercel AI SDK

Use Cardly MCP with Vercel AI SDK

Mastra AI

Mastra AI

Use Cardly MCP with Mastra AI

LlamaIndex

LlamaIndex

Use Cardly MCP with LlamaIndex

CrewAI

CrewAI

Use Cardly MCP with CrewAI

FAQ

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

With a standalone Cardly MCP server, the agents and LLMs can only access a fixed set of Cardly tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Cardly 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 Cardly tools.

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

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

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