How to integrate Textit MCP with OpenAI Agents SDK

This guide walks you through connecting Textit to the OpenAI Agents SDK using the Composio tool router. By the end, you'll have a working Textit agent that can create a new campaign for event reminders, list all contact groups for segmentation, retrieve details about a specific campaign through natural language commands. This guide will help you understand how to give your OpenAI Agents SDK agent real control over a Textit account through Composio's Textit MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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31 Tools

Introduction

This guide walks you through connecting Textit to the OpenAI Agents SDK using the Composio tool router. By the end, you'll have a working Textit agent that can create a new campaign for event reminders, list all contact groups for segmentation, retrieve details about a specific campaign through natural language commands.

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

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

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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 Textit
  • Configure an AI agent that can use Textit as a tool
  • Run a live chat session where you can ask the agent to perform Textit 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 Textit MCP server, and what's possible with it?

The Textit MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Textit account. It provides structured and secure access to your chatbots, contacts, campaigns, and messaging flows, so your agent can create campaigns, manage contact groups, organize labels, retrieve broadcasts, and handle messaging operations on your behalf.

  • Automated campaign management: Let your agent create, retrieve, or list messaging campaigns, helping you launch outreach efforts to targeted contact groups without lifting a finger.
  • Contact group creation and segmentation: Easily segment your audience by having your agent create or delete contact groups, keeping your communication organized and relevant.
  • Custom label organization: Enable your agent to create new message labels, allowing for smarter categorization and easier tracking of important conversations or topics.
  • Broadcast and archive retrieval: Effortlessly fetch lists of broadcasts or message archives, so your agent can provide summaries or analyze past messaging performance.
  • Contact management: Direct your agent to delete outdated or unnecessary contacts, ensuring your database stays clean and up-to-date automatically.

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 Textit 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 Textit.
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 Textit
const session = await composio.create(userId as string, {
  toolkits: ['textit'],
});
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 textit.
  • The router checks the user's Textit connection and prepares the MCP endpoint.
  • The returned session.mcp.url is the MCP URL that your agent will use to access Textit.
  • This approach keeps things lightweight and lets the agent request Textit 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 Textit. Help users perform Textit 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 Textit 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 Textit 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 Textit.
  • 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 Textit 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: ['textit'],
  });
  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 Textit. Help users perform Textit 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 Textit MCP with OpenAI Agents SDK to build a functional AI agent that can interact with Textit.

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 Textit action and event your agent gets out of the box.

Create Campaign

Tool to create a new campaign in TextIt.

Create Contact Group

Tool to create a new contact group.

Create Label

Tool to create a new message label.

Delete Contact

Tool to delete an existing contact.

Delete Contact Group

Tool to delete an existing contact group.

Delete Label

Tool to delete a message label by UUID.

Get Campaign

Tool to retrieve details about a specific campaign.

Get Workspace

Tool to retrieve current workspace details including name, country, languages, and timezone.

List Archives

Tool to retrieve a list of message and run archives.

List Broadcasts

Tool to list broadcasts.

List Campaign Events 2

Tool to retrieve campaign events with optional filtering.

List Campaigns

Tool to list campaigns.

List Channels

Tool to list channels.

List Classifiers

Tool to list NLU classifiers configured for your organization.

List Contacts

Tool to retrieve a list of contacts.

List custom contact fields

Tool to retrieve a list of custom contact fields.

List Flows

Tool to retrieve a list of flows for your organization.

List Flow Starts

Tool to retrieve a list of manual flow starts.

List Globals

Tool to list global variables.

List Groups

Tool to list contact groups for your organization.

List Labels 2

Tool to retrieve a list of message labels for your organization.

List Messages

Tool to retrieve a list of messages.

List Resthook Events

Tool to retrieve recent resthook events for your organization.

List Resthooks

Tool to list configured resthooks (webhooks).

List Resthook Subscribers

Tool to list webhook subscribers for your organization's resthooks.

List Runs

Tool to retrieve a list of flow runs.

List Tickets

Tool to retrieve support tickets for your organization.

List Topics V2

Tool to list topics in the workspace for categorizing tickets.

List Users

Tool to retrieve a list of user logins in your workspace with their roles and teams.

Send Broadcast

Tool to send a new broadcast message.

Update Contact

Tool to update an existing contact.

FAQ

Frequently asked questions

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

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

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