How to integrate Request Tracker (RT) MCP with OpenAI Agents SDK

This guide walks you through connecting Request Tracker (RT) to the OpenAI Agents SDK using the Composio tool router. By the end, you'll have a working Request Tracker (RT) agent that can search your support tickets, create tickets, review ticket history, reply to tickets, and update tickets through natural language commands. This guide will help you understand how to give your OpenAI Agents SDK agent real control over a Request Tracker (RT) account through Composio's Request Tracker (RT) MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

Request Tracker (RT) logoRequest Tracker (RT)
Api Key

Request Tracker (RT) is a ticketing and workflow platform for managing support requests, queues, users, assets, and knowledge articles. It helps support and operations teams track work, enforce process, and keep request history in one place.

11 Tools

Introduction

This guide walks you through connecting Request Tracker (RT) to the OpenAI Agents SDK using the Composio tool router. By the end, you'll have a working Request Tracker (RT) agent that can search your support tickets, create tickets, review ticket history, reply to tickets, and update tickets through natural language commands.

This guide will help you understand how to give your OpenAI Agents SDK agent real control over a Request Tracker (RT) account through Composio's Request Tracker (RT) MCP server.

Before we dive in, let's take a quick look at the key ideas and tools involved.

Also integrate Request Tracker (RT) with

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 Request Tracker (RT)
  • Configure an AI agent that can use Request Tracker (RT) as a tool
  • Run a live chat session where you can ask the agent to perform Request Tracker (RT) operations

What is OpenAI 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 Request Tracker (RT) MCP server, and what's possible with it?

The Request Tracker (RT) MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Request Tracker (RT) account. It provides structured and secure access to your tickets, queues, users, ticket histories, and attachment details, so your agent can search, create, review, update, and respond to tickets on your behalf.

  • Ticket search and review: Have your agent find tickets using specific criteria and retrieve their current details for quick review.
  • Ticket creation and updates: Direct your agent to create tickets in the right queue or update selected ticket details as work progresses.
  • Replies and internal comments: Let the agent send public replies to requesters or add private comments for your support team.
  • Queue and user lookup: Instruct your agent to browse available queues and find users when choosing ticket requesters or owners.
  • History and attachment review: Have your agent review ticket activity, field changes, comments, timestamps, and available attachment details.

What is the Composio tool router, and how does it fit here?

What is Composio SDK?

Composio's Composio SDK 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 Composio SDK

The tool router generates a secure MCP URL that your agents can access to perform actions.

How the Composio SDK works

The Composio SDK 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

Step by step09 STEPS
1

Prerequisites

Before starting, make sure you have:
  • Composio API Key and OpenAI API Key
  • Primary know-how of OpenAI Agents SDK
  • A live Request Tracker (RT) project
  • Some knowledge of Python or Typescript
2

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
3

Install dependencies

npm install @composio/openai-agents @openai/agents dotenv

Install the Composio SDK and the OpenAI Agents SDK.

4

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.

5

Import dependencies

import 'dotenv/config';
import { Composio } from '@composio/core';
import { OpenAIAgentsProvider } from '@composio/openai-agents';
import { Agent, hostedMcpTool, run, OpenAIConversationsSession } from '@openai/agents';
import * as readline from 'readline';
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 Request Tracker (RT).
6

Set up the Composio instance

dotenv.config();

const composioApiKey = process.env.COMPOSIO_API_KEY;
const userId = process.env.USER_ID;

if (!composioApiKey) {
  throw new Error('COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key');
}
if (!userId) {
  throw new Error('USER_ID is not set');
}

// Initialize Composio
const composio = new Composio({
  apiKey: composioApiKey,
  provider: new OpenAIAgentsProvider(),
});
What's happening:
  • dotenv.config() loads your .env file so COMPOSIO_API_KEY and USER_ID are available as environment variables.
  • Creating a Composio instance using the API Key and OpenAIAgentsProvider class.
7

Create a Tool Router session

// Create Tool Router session for Request Tracker (RT)
const session = await composio.create(userId as string, {
  toolkits: ['request_tracker'],
});
const mcpUrl = session.mcp.url;

What is happening:

  • You give the Tool Router the user id and the toolkits you want available. Here, it is only request_tracker.
  • The router checks the user's Request Tracker (RT) connection and prepares the MCP endpoint.
  • The returned session.mcp.url is the MCP URL that your agent will use to access Request Tracker (RT).
  • This approach keeps things lightweight and lets the agent request Request Tracker (RT) tools only when needed during the conversation.
8

Configure the agent

// Configure agent with MCP tool
const agent = new Agent({
  name: 'Assistant',
  model: 'gpt-5',
  instructions:
    'You are a helpful assistant that can access Request Tracker (RT). Help users perform Request Tracker (RT) operations through natural language.',
  tools: [
    hostedMcpTool({
      serverLabel: 'tool_router',
      serverUrl: mcpUrl,
      headers: { 'x-api-key': composioApiKey },
      requireApproval: '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 Request Tracker (RT) 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 object includes the Composio API key for secure authentication with the MCP server.
  • requireApproval: 'never' means the agent can execute Request Tracker (RT) operations without asking for permission each time, making interactions smoother.
9

Start chat loop and handle conversation

// Keep conversation state across turns
const conversationSession = new OpenAIConversationsSession();

// Simple CLI
const rl = readline.createInterface({
  input: process.stdin,
  output: process.stdout,
  prompt: 'You: ',
});

console.log('\nComposio Tool Router session created.');
console.log('\nChat started. Type your requests below.');
console.log("Commands: 'exit', 'quit', or 'q' to end\n");

try {
  const first = await run(agent, 'What can you help me with?', { session: conversationSession });
  console.log(`Assistant: ${first.finalOutput}\n`);
} catch (e) {
  console.error('Error:', e instanceof Error ? e.message : e, '\n');
}

rl.prompt();

rl.on('line', async (userInput) => {
  const text = userInput.trim();

  if (['exit', 'quit', 'q'].includes(text.toLowerCase())) {
    console.log('Goodbye!');
    rl.close();
    process.exit(0);
  }

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

  try {
    const result = await run(agent, text, { session: conversationSession });
    console.log(`\nAssistant: ${result.finalOutput}\n`);
  } catch (e) {
    console.error('Error:', e instanceof Error ? e.message : e, '\n');
  }

  rl.prompt();
});

rl.on('close', () => {
  console.log('\n👋 Session ended.');
  process.exit(0);
});
What's happening:
  • The program prints a session URL that you visit to authorize Request Tracker (RT).
  • After authorization, the chat begins.
  • Each message you type is processed by the agent using run().
  • The responses are printed to the console.
  • Typing exit, quit, or q cleanly ends the chat.

Complete Code

Here's the complete code to get you started with Request Tracker (RT) and OpenAI Agents SDK:

import 'dotenv/config';
import { Composio } from '@composio/core';
import { OpenAIAgentsProvider } from '@composio/openai-agents';
import { Agent, hostedMcpTool, run, OpenAIConversationsSession } from '@openai/agents';
import * as readline from 'readline';

const composioApiKey = process.env.COMPOSIO_API_KEY;
const userId = process.env.USER_ID;

if (!composioApiKey) {
  throw new Error('COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key');
}
if (!userId) {
  throw new Error('USER_ID is not set');
}

// Initialize Composio
const composio = new Composio({
  apiKey: composioApiKey,
  provider: new OpenAIAgentsProvider(),
});

async function main() {
  // Create Tool Router session
  const session = await composio.create(userId as string, {
    toolkits: ['request_tracker'],
  });
  const mcpUrl = session.mcp.url;

  // Configure agent with MCP tool
  const agent = new Agent({
    name: 'Assistant',
    model: 'gpt-5',
    instructions:
      'You are a helpful assistant that can access Request Tracker (RT). Help users perform Request Tracker (RT) operations through natural language.',
    tools: [
      hostedMcpTool({
        serverLabel: 'tool_router',
        serverUrl: mcpUrl,
        headers: { 'x-api-key': composioApiKey },
        requireApproval: 'never',
      }),
    ],
  });

  // Keep conversation state across turns
  const conversationSession = new OpenAIConversationsSession();

  // Simple CLI
  const rl = readline.createInterface({
    input: process.stdin,
    output: process.stdout,
    prompt: 'You: ',
  });

  console.log('\nComposio Tool Router session created.');
  console.log('\nChat started. Type your requests below.');
  console.log("Commands: 'exit', 'quit', or 'q' to end\n");

  try {
    const first = await run(agent, 'What can you help me with?', { session: conversationSession });
    console.log(`Assistant: ${first.finalOutput}\n`);
  } catch (e) {
    console.error('Error:', e instanceof Error ? e.message : e, '\n');
  }

  rl.prompt();

  rl.on('line', async (userInput) => {
    const text = userInput.trim();

    if (['exit', 'quit', 'q'].includes(text.toLowerCase())) {
      console.log('Goodbye!');
      rl.close();
      process.exit(0);
    }

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

    try {
      const result = await run(agent, text, { session: conversationSession });
      console.log(`\nAssistant: ${result.finalOutput}\n`);
    } catch (e) {
      console.error('Error:', e instanceof Error ? e.message : e, '\n');
    }

    rl.prompt();
  });

  rl.on('close', () => {
    console.log('\nSession ended.');
    process.exit(0);
  });
}

main().catch((err) => {
  console.error('Fatal error:', err);
  process.exit(1);
});

Conclusion

This was a starter code for integrating Request Tracker (RT) MCP with OpenAI Agents SDK to build a functional AI agent that can interact with Request Tracker (RT).

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.
TOOLS

Supported Tools

Every Request Tracker (RT) action and event your agent gets out of the box.

Add Ticket Comment

Add a private internal comment to an RT ticket.

Create Ticket

Create a durable RT ticket in a queue.

Get Queue

Retrieve one visible RT queue by id or exact name, including lifecycle and capability-sensitive links.

Get Ticket

Retrieve one visible RT ticket, including its current fields and capability-sensitive links for allowed follow-up operations.

Get Ticket History

Return one page of detailed ticket history, including transaction types, field changes, comments, creators, and timestamps.

List Queues

List queues visible to the connected RT user so an agent can select a queue for ticket search or creation.

List Ticket Attachments

List attachment metadata references associated with a visible RT ticket without downloading attachment content.

Reply to Ticket

Send public correspondence on an RT ticket.

Search Tickets

Search visible RT tickets with an explicit TicketSQL expression and return one bounded page.

Search Users

Search RT users with structured field conditions and return one bounded page of user references or selected fields for requester and owner lookup.

Update Ticket

Update selected metadata on an existing RT ticket and verify every requested field by reading it back.

FAQ

Frequently asked questions

With a standalone Request Tracker (RT) MCP server, the agents and LLMs can only access a fixed set of Request Tracker (RT) tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Request Tracker (RT) and many other apps based on the task at hand, all through a single MCP endpoint.

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 Request Tracker (RT) tools.

Yes, absolutely. You can configure which Request Tracker (RT) 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.

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 Request Tracker (RT) data and credentials are handled as safely as possible.

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