How to integrate Supportbee MCP with Autogen

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Introduction

This guide walks you through connecting Supportbee to AutoGen 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 AutoGen 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 required dependencies for Autogen and Composio
  • Initialize Composio and create a Tool Router session for Supportbee
  • Wire that MCP URL into Autogen using McpWorkbench and StreamableHttpServerParams
  • Configure an Autogen AssistantAgent that can call Supportbee tools
  • Run a live chat loop where you ask the agent to perform Supportbee 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 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

You will need:

  • A Composio API key
  • An OpenAI API key (used by Autogen's OpenAIChatCompletionClient)
  • A Supportbee account you can connect to Composio
  • Some basic familiarity with Autogen and Python async

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.

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 Supportbee via MCP
  • autogen-agentchat provides the AssistantAgent class
  • autogen-ext-openai provides the OpenAI model client
  • autogen-ext-tools provides MCP workbench support

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 Supportbee connections to use

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 Supportbee session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["supportbee"]
    )
    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 Supportbee tools
  • session.mcp.url is the MCP endpoint that Autogen will connect to

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

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 Supportbee assistant agent with MCP tools
    agent = AssistantAgent(
        name="supportbee_assistant",
        description="An AI assistant that helps with Supportbee 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 Supportbee tools from the workbench

Run the interactive chat loop

python
print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
print("Ask any Supportbee 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 Supportbee 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 Supportbee 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 Supportbee session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["supportbee"]
    )
    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 Supportbee assistant agent with MCP tools
        agent = AssistantAgent(
            name="supportbee_assistant",
            description="An AI assistant that helps with Supportbee 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 Supportbee 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 Supportbee 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 Supportbee, you can reuse the same structure for other MCP-enabled apps with minimal code changes.

How to build Supportbee MCP Agent with another framework

OpenAI Agents SDK

OpenAI Agents SDK

Use Supportbee MCP with OpenAI Agents SDK

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 Autogen?

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 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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