How to integrate Supportbee MCP with Mastra AI

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Introduction

This guide walks you through connecting Supportbee to Mastra AI 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 Mastra AI 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:
  • Set up your environment so Mastra, OpenAI, and Composio work together
  • Create a Tool Router session in Composio that exposes Supportbee tools
  • Connect Mastra's MCP client to the Composio generated MCP URL
  • Fetch Supportbee tool definitions and attach them as a toolset
  • Build a Mastra agent that can reason, call tools, and return structured results
  • Run an interactive CLI where you can chat with your Supportbee agent

What is Mastra AI?

Mastra AI is a TypeScript framework for building AI agents with tool support. It provides a clean API for creating agents that can use external services through MCP.

Key features include:

  • MCP Client: Built-in support for Model Context Protocol servers
  • Toolsets: Organize tools into logical groups
  • Step Callbacks: Monitor and debug agent execution
  • OpenAI Integration: Works with OpenAI models via @ai-sdk/openai

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:
  • Node.js 18 or higher
  • A Composio account with an active API key
  • An OpenAI API key
  • Basic familiarity with TypeScript

Getting API Keys for OpenAI and Composio

OpenAI API Key
  • Go to the OpenAI dashboard and create an API key.
  • You need credits or a connected billing setup to use the models.
  • Store the key somewhere safe.
Composio API Key
  • Log in to the Composio dashboard.
  • Go to Settings and copy your API key.
  • This key lets your Mastra agent talk to Composio and reach Supportbee through MCP.

Install dependencies

bash
npm install @composio/core @mastra/core @mastra/mcp @ai-sdk/openai dotenv

Install the required packages.

What's happening:

  • @composio/core is the Composio SDK for creating MCP sessions
  • @mastra/core provides the Agent class
  • @mastra/mcp is Mastra's MCP client
  • @ai-sdk/openai is the model wrapper for OpenAI
  • dotenv loads environment variables from .env

Set up environment variables

bash
COMPOSIO_API_KEY=your_composio_api_key_here
COMPOSIO_USER_ID=your_user_id_here
OPENAI_API_KEY=your_openai_api_key_here

Create a .env file in your project root.

What's happening:

  • COMPOSIO_API_KEY authenticates your requests to Composio
  • COMPOSIO_USER_ID tells Composio which user this session belongs to
  • OPENAI_API_KEY lets the Mastra agent call OpenAI models

Import libraries and validate environment

typescript
import "dotenv/config";
import { openai } from "@ai-sdk/openai";
import { Agent } from "@mastra/core/agent";
import { MCPClient } from "@mastra/mcp";
import { Composio } from "@composio/core";
import * as readline from "readline";

import type { AiMessageType } from "@mastra/core/agent";

const openaiAPIKey = process.env.OPENAI_API_KEY;
const composioAPIKey = process.env.COMPOSIO_API_KEY;
const composioUserID = process.env.COMPOSIO_USER_ID;

if (!openaiAPIKey) throw new Error("OPENAI_API_KEY is not set");
if (!composioAPIKey) throw new Error("COMPOSIO_API_KEY is not set");
if (!composioUserID) throw new Error("COMPOSIO_USER_ID is not set");

const composio = new Composio({
  apiKey: composioAPIKey as string,
});
What's happening:
  • dotenv/config auto loads your .env so process.env.* is available
  • openai gives you a Mastra compatible model wrapper
  • Agent is the Mastra agent that will call tools and produce answers
  • MCPClient connects Mastra to your Composio MCP server
  • Composio is used to create a Tool Router session

Create a Tool Router session for Supportbee

typescript
async function main() {
  const session = await composio.create(
    composioUserID as string,
    {
      toolkits: ["supportbee"],
    },
  );

  const composioMCPUrl = session.mcp.url;
  console.log("Supportbee MCP URL:", composioMCPUrl);
What's happening:
  • create spins up a short-lived MCP HTTP endpoint for this user
  • The toolkits array contains "supportbee" for Supportbee access
  • session.mcp.url is the MCP URL that Mastra's MCPClient will connect to

Configure Mastra MCP client and fetch tools

typescript
const mcpClient = new MCPClient({
    id: composioUserID as string,
    servers: {
      nasdaq: {
        url: new URL(composioMCPUrl),
        requestInit: {
          headers: session.mcp.headers,
        },
      },
    },
    timeout: 30_000,
  });

console.log("Fetching MCP tools from Composio...");
const composioTools = await mcpClient.getTools();
console.log("Number of tools:", Object.keys(composioTools).length);
What's happening:
  • MCPClient takes an id for this client and a list of MCP servers
  • The headers property includes the x-api-key for authentication
  • getTools fetches the tool definitions exposed by the Supportbee toolkit

Create the Mastra agent

typescript
const agent = new Agent({
    name: "supportbee-mastra-agent",
    instructions: "You are an AI agent with Supportbee tools via Composio.",
    model: "openai/gpt-5",
  });
What's happening:
  • Agent is the core Mastra agent
  • name is just an identifier for logging and debugging
  • instructions guide the agent to use tools instead of only answering in natural language
  • model uses openai("gpt-5") to configure the underlying LLM

Set up interactive chat interface

typescript
let messages: AiMessageType[] = [];

console.log("Chat started! Type 'exit' or 'quit' to end.\n");

const rl = readline.createInterface({
  input: process.stdin,
  output: process.stdout,
  prompt: "> ",
});

rl.prompt();

rl.on("line", async (userInput: string) => {
  const trimmedInput = userInput.trim();

  if (["exit", "quit", "bye"].includes(trimmedInput.toLowerCase())) {
    console.log("\nGoodbye!");
    rl.close();
    process.exit(0);
  }

  if (!trimmedInput) {
    rl.prompt();
    return;
  }

  messages.push({
    id: crypto.randomUUID(),
    role: "user",
    content: trimmedInput,
  });

  console.log("\nAgent is thinking...\n");

  try {
    const response = await agent.generate(messages, {
      toolsets: {
        supportbee: composioTools,
      },
      maxSteps: 8,
    });

    const { text } = response;

    if (text && text.trim().length > 0) {
      console.log(`Agent: ${text}\n`);
        messages.push({
          id: crypto.randomUUID(),
          role: "assistant",
          content: text,
        });
      }
    } catch (error) {
      console.error("\nError:", error);
    }

    rl.prompt();
  });

  rl.on("close", async () => {
    console.log("\nSession ended.");
    await mcpClient.disconnect();
    process.exit(0);
  });
}

main().catch((err) => {
  console.error("Fatal error:", err);
  process.exit(1);
});
What's happening:
  • messages keeps the full conversation history in Mastra's expected format
  • agent.generate runs the agent with conversation history and Supportbee toolsets
  • maxSteps limits how many tool calls the agent can take in a single run
  • onStepFinish is a hook that prints intermediate steps for debugging

Complete Code

Here's the complete code to get you started with Supportbee and Mastra AI:

typescript
import "dotenv/config";
import { openai } from "@ai-sdk/openai";
import { Agent } from "@mastra/core/agent";
import { MCPClient } from "@mastra/mcp";
import { Composio } from "@composio/core";
import * as readline from "readline";

import type { AiMessageType } from "@mastra/core/agent";

const openaiAPIKey = process.env.OPENAI_API_KEY;
const composioAPIKey = process.env.COMPOSIO_API_KEY;
const composioUserID = process.env.COMPOSIO_USER_ID;

if (!openaiAPIKey) throw new Error("OPENAI_API_KEY is not set");
if (!composioAPIKey) throw new Error("COMPOSIO_API_KEY is not set");
if (!composioUserID) throw new Error("COMPOSIO_USER_ID is not set");

const composio = new Composio({ apiKey: composioAPIKey as string });

async function main() {
  const session = await composio.create(composioUserID as string, {
    toolkits: ["supportbee"],
  });

  const composioMCPUrl = session.mcp.url;

  const mcpClient = new MCPClient({
    id: composioUserID as string,
    servers: {
      supportbee: {
        url: new URL(composioMCPUrl),
        requestInit: {
          headers: session.mcp.headers,
        },
      },
    },
    timeout: 30_000,
  });

  const composioTools = await mcpClient.getTools();

  const agent = new Agent({
    name: "supportbee-mastra-agent",
    instructions: "You are an AI agent with Supportbee tools via Composio.",
    model: "openai/gpt-5",
  });

  let messages: AiMessageType[] = [];

  const rl = readline.createInterface({
    input: process.stdin,
    output: process.stdout,
    prompt: "> ",
  });

  rl.prompt();

  rl.on("line", async (input: string) => {
    const trimmed = input.trim();
    if (["exit", "quit"].includes(trimmed.toLowerCase())) {
      rl.close();
      return;
    }

    messages.push({ id: crypto.randomUUID(), role: "user", content: trimmed });

    const { text } = await agent.generate(messages, {
      toolsets: { supportbee: composioTools },
      maxSteps: 8,
    });

    if (text) {
      console.log(`Agent: ${text}\n`);
      messages.push({ id: crypto.randomUUID(), role: "assistant", content: text });
    }

    rl.prompt();
  });

  rl.on("close", async () => {
    await mcpClient.disconnect();
    process.exit(0);
  });
}

main();

Conclusion

You've built a Mastra AI agent that can interact with Supportbee through Composio's Tool Router. You can extend this further by:
  • Adding other toolkits like Gmail, Slack, or GitHub
  • Building a web-based chat interface around this agent
  • Using multiple MCP endpoints to enable cross-app workflows

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

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 Mastra AI?

Yes, you can. Mastra AI 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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