How to integrate Textit MCP with Mastra AI

This guide walks you through connecting Textit to Mastra AI 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 Mastra AI 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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Textit is a platform for building scalable, interactive chatbots across multiple channels—no coding required. It helps businesses automate communication, collect data, and manage chat workflows effortlessly.

31 Tools

Introduction

This guide walks you through connecting Textit to Mastra AI 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 Mastra AI 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:
  • Set up your environment so Mastra, OpenAI, and Composio work together
  • Create a Tool Router session in Composio that exposes Textit tools
  • Connect Mastra's MCP client to the Composio generated MCP URL
  • Fetch Textit 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 Textit 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 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:
  • Node.js 18 or higher
  • A Composio account with an active API key
  • An OpenAI API key
  • Basic familiarity with TypeScript
2

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 Textit through MCP.
3

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
4

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
5

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
6

Create a Tool Router session for Textit

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

  const composioMCPUrl = session.mcp.url;
  console.log("Textit MCP URL:", composioMCPUrl);
What's happening:
  • create spins up a short-lived MCP HTTP endpoint for this user
  • The toolkits array contains "textit" for Textit access
  • session.mcp.url is the MCP URL that Mastra's MCPClient will connect to
7

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 Textit toolkit
8

Create the Mastra agent

typescript
const agent = new Agent({
    name: "textit-mastra-agent",
    instructions: "You are an AI agent with Textit 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
9

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: {
        textit: 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 Textit 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 Textit 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: ["textit"],
  });

  const composioMCPUrl = session.mcp.url;

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

  const composioTools = await mcpClient.getTools();

  const agent = new Agent({
    name: "textit-mastra-agent",
    instructions: "You are an AI agent with Textit 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: { textit: 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 Textit 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
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. 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 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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