How to integrate Supportbee MCP with OpenAI Agents SDK

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Introduction

This guide walks you through connecting Supportbee to the OpenAI Agents SDK using the Composio tool router. By the end, you'll have a working Supportbee agent that can archive all tickets resolved this week, assign new tickets to the support team, create a reusable snippet for refund replies, reply to the oldest open ticket with a template through natural language commands.

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

The Supportbee MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Supportbee account. It provides structured and secure access to your support ticketing system, so your agent can perform actions like creating and replying to tickets, managing team assignments, organizing tickets, and automating support workflows on your behalf.

  • Automated ticket creation and updates: Instantly open new support tickets, update their content, or post replies to customer inquiries without leaving your workflow.
  • Team assignment and ticket routing: Direct your agent to assign tickets to the right team or agent, ensuring every request is handled by the appropriate group.
  • Archiving and deleting tickets: Keep your helpdesk organized by having the agent archive resolved tickets or permanently remove unwanted ones from the system.
  • Reusable response snippets: Let your agent create, manage, and delete response templates so your team can reply faster and more consistently.
  • Rule-based workflow automation: Empower your agent to create new automation rules that streamline ticket routing, escalation, and handling based on custom conditions.

Supported Tools & Triggers

Tools
Archive SupportBee TicketTool to archive a supportbee ticket by its id.
Assign Ticket to TeamTool to assign a ticket to a team.
Create RuleTool to create a new routing or automation rule in supportbee.
Create SnippetTool to create a reusable snippet for ticket responses.
Create SupportBee TicketTool to create a new support ticket.
Create Ticket ReplyTool to post a reply to a ticket.
Create SupportBee UserTool to create a new user in supportbee.
Delete SnippetTool to delete a snippet by its id.
Delete SupportBee TicketTool to permanently delete a trashed ticket.
Fetch EmailsTool to retrieve all forwarding email addresses for the company.
Fetch SupportBee LabelsTool to retrieve all custom labels.
Fetch SnippetsTool to fetch all saved snippets.
Fetch SupportBee Team by IDTool to fetch a supportbee team by its id.
Fetch SupportBee TeamsTool to retrieve all teams in the company.
Get Avg First Response Time ReportTool to retrieve average first response time data points.
Get Replies Count ReportTool to get replies count data points over time.
Get Tickets Count ReportTool to get ticket count data points over time.
List Ticket CommentsTool to list all comments for a ticket.
List Ticket RepliesTool to list all replies for a specific ticket.
List TicketsTool to list tickets.
Mark SupportBee Ticket as AnsweredTool to mark a ticket as answered.
Mark SupportBee Ticket as SpamTool to mark a supportbee ticket as spam.
Mark SupportBee Ticket as UnansweredTool to mark a ticket as unanswered.
Search SupportBee TicketsTool to search supportbee tickets.
Show Ticket ReplyTool to fetch a specific reply for a supportbee ticket.
Show SupportBee User or Customer GroupTool to retrieve a user or customer group by id.
Trash SupportBee TicketTool to trash a supportbee ticket by its id.
Unarchive SupportBee TicketTool to unarchive a supportbee ticket by its id.
Unassign Ticket from TeamTool to un-assign a ticket from its assigned team.
Unassign User From TicketTool to unassign the user from a ticket.
Unmark SupportBee Ticket as SpamTool to unmark a supportbee ticket as spam.
Untrash SupportBee TicketTool to untrash (restore) a supportbee ticket by its id.
Update SupportBee UserUpdate supportbee user

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 Supportbee 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 Supportbee.

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 Supportbee Tool Router session
session = composio.create(
    user_id=user_id,
    toolkits=["supportbee"]
)

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

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 Supportbee MCP Agent with another framework

Claude Agent SDK

Claude Agent SDK

Use Supportbee MCP with Claude Agent SDK

Google ADK

Google ADK

Use Supportbee MCP with Google ADK

LangChain

LangChain

Use Supportbee MCP with LangChain

Vercel AI SDK

Vercel AI SDK

Use Supportbee MCP with Vercel AI SDK

Mastra AI

Mastra AI

Use Supportbee MCP with Mastra AI

LlamaIndex

LlamaIndex

Use Supportbee MCP with LlamaIndex

CrewAI

CrewAI

Use Supportbee MCP with CrewAI

FAQ

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

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

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

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

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