How to integrate Customerio MCP with OpenAI Agents SDK

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Introduction

This guide walks you through connecting Customerio to the OpenAI Agents SDK using the Composio tool router. By the end, you'll have a working Customerio agent that can list all segments in my workspace, get delivery metrics for last week's emails, show all people in vip customer segment, retrieve all webhooks configured in workspace through natural language commands.

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

The Customerio MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Customer.io account. It provides structured and secure access to your customer engagement workspace, allowing your agent to send targeted communications, manage segments, retrieve messaging analytics, and automate customer data management on your behalf.

  • Targeted message analytics and tracking: Retrieve detailed lists of messages sent, including delivery metrics, to monitor campaign performance and engagement.
  • Segment discovery and membership management: Let your agent fetch all segments, get details for a specific segment, and list all customers in a segment for precise audience targeting.
  • Integration and webhook management: Have your agent list and review all integrations and webhooks in your workspace to streamline system connectivity and reporting.
  • Customer profile suppression: Direct your agent to permanently suppress (delete and block) customer profiles, ensuring compliance and data privacy.
  • Collection metadata retrieval: Retrieve up-to-date details for all collections in your workspace, keeping your AI-powered workflows and automations in sync with your data sources.

Supported Tools & Triggers

Tools
Suppress Customer ProfileTool to suppress a person.
Get IntegrationsTool to retrieve a list of integrations in your workspace.
Get MessagesTool to retrieve a list of messages sent from your workspace.
Get Segment DetailsTool to retrieve details of a specific segment.
Get Segment MembershipTool to retrieve people in a specific segment.
Get SegmentsTool to retrieve a list of segments in your workspace.
Get TriggerTool to retrieve details about a specific trigger.
Get TriggersTool to retrieve a list of triggers for a specific broadcast.
Get Customer.io Workspace WebhooksTool to retrieve a list of webhooks.
List CollectionsTool to list all collections metadata.
List NewslettersTool to list all newsletters.
List SnippetsTool to list all snippets in your workspace.
List Transactional MessagesTool to list all transactional message templates.
Trigger BroadcastTool to manually trigger a broadcast.

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 Customerio 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 Customerio.

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 Customerio Tool Router session
session = composio.create(
    user_id=user_id,
    toolkits=["customerio"]
)

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

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 Customerio MCP Agent with another framework

Claude Agent SDK

Claude Agent SDK

Use Customerio MCP with Claude Agent SDK

Google ADK

Google ADK

Use Customerio MCP with Google ADK

LangChain

LangChain

Use Customerio MCP with LangChain

Vercel AI SDK

Vercel AI SDK

Use Customerio MCP with Vercel AI SDK

Mastra AI

Mastra AI

Use Customerio MCP with Mastra AI

LlamaIndex

LlamaIndex

Use Customerio MCP with LlamaIndex

CrewAI

CrewAI

Use Customerio MCP with CrewAI

FAQ

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

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

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

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

Used by agents from

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

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