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How to integrate Textit MCP with CrewAI

Connect CrewAI to Textit MCP. Create a new campaign for event reminders, list all contact groups for segmentation, and more using natural language, with authentication handled for you.

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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 CrewAI using the Composio tool router. By the end, you'll have a working Textit agent that can send broadcasts, list contacts and messages, manage contact groups and labels, create campaigns, and review flow runs through natural language commands.

This guide will help you understand how to give your CrewAI 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.

Also integrate Textit with

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TL;DR

Here's what you'll learn:
  • Get a Composio API key and configure your Textit connection
  • Set up CrewAI with an MCP enabled agent
  • Create a Tool Router session or standalone MCP server for Textit
  • Build a conversational loop where your agent can execute Textit operations

What is CrewAI?

CrewAI is a powerful framework for building multi-agent AI systems. It provides primitives for defining agents with specific roles, creating tasks, and orchestrating workflows through crews.

Key features include:

  • Agent Roles: Define specialized agents with specific goals and backstories
  • Task Management: Create tasks with clear descriptions and expected outputs
  • Crew Orchestration: Combine agents and tasks into collaborative workflows
  • MCP Integration: Connect to external tools through Model Context Protocol

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 step08 STEPS
1

Prerequisites

Before starting, make sure you have:
  • Python 3.9 or higher
  • A Composio account and API key
  • A Textit connection authorized in Composio
  • An OpenAI API key for the CrewAI LLM
  • Basic familiarity with Python
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
  • 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.
3

Install dependencies

bash
pip install composio crewai crewai-tools[mcp] python-dotenv
What's happening:
  • composio connects your agent to Textit via MCP
  • crewai provides Agent, Task, Crew, and LLM primitives
  • crewai-tools[mcp] includes MCP helpers
  • python-dotenv loads environment variables from .env
4

Set up environment variables

bash
COMPOSIO_API_KEY=your_composio_api_key_here
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 with Composio
  • USER_ID scopes the session to your account
  • OPENAI_API_KEY lets CrewAI use your chosen OpenAI model
5

Import dependencies

python
import os
from composio import Composio
from crewai import Agent, Task, Crew
from crewai_tools import MCPServerAdapter
import dotenv

dotenv.load_dotenv()

COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY")
COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID")

if not COMPOSIO_API_KEY:
    raise ValueError("COMPOSIO_API_KEY is not set")
if not COMPOSIO_USER_ID:
    raise ValueError("COMPOSIO_USER_ID is not set")
What's happening:
  • CrewAI classes define agents and tasks, and run the workflow
  • MCPServerHTTP connects the agent to an MCP endpoint
  • Composio will give you a short lived Textit MCP URL
6

Create a Composio Tool Router session for Textit

python
composio_client = Composio(api_key=COMPOSIO_API_KEY)
session = composio_client.create(user_id=COMPOSIO_USER_ID, toolkits=["textit"])

url = session.mcp.url
What's happening:
  • You create a Textit only session through Composio
  • Composio returns an MCP HTTP URL that exposes Textit tools
7

Initialize the MCP Server

python
server_params = {
    "url": url,
    "transport": "streamable-http",
    "headers": {"x-api-key": COMPOSIO_API_KEY},
}

with MCPServerAdapter(server_params) as tools:
    agent = Agent(
        role="Search Assistant",
        goal="Help users search the internet effectively",
        backstory="You are a helpful assistant with access to search tools.",
        tools=tools,
        verbose=False,
        max_iter=10,
    )
What's Happening:
  • Server Configuration: The code sets up connection parameters including the MCP server URL, streamable HTTP transport, and Composio API key authentication.
  • MCP Adapter Bridge: MCPServerAdapter acts as a context manager that converts Composio MCP tools into a CrewAI-compatible format.
  • Agent Setup: Creates a CrewAI Agent with a defined role (Search Assistant), goal (help with internet searches), and access to the MCP tools.
  • Configuration Options: The agent includes settings like verbose=False for clean output and max_iter=10 to prevent infinite loops.
  • Dynamic Tool Usage: Once created, the agent automatically accesses all Composio Search tools and decides when to use them based on user queries.
8

Create a CLI Chatloop and define the Crew

python
print("Chat started! Type 'exit' or 'quit' to end.\n")

conversation_context = ""

while True:
    user_input = input("You: ").strip()

    if user_input.lower() in ["exit", "quit", "bye"]:
        print("\nGoodbye!")
        break

    if not user_input:
        continue

    conversation_context += f"\nUser: {user_input}\n"
    print("\nAgent is thinking...\n")

    task = Task(
        description=(
            f"Conversation history:\n{conversation_context}\n\n"
            f"Current request: {user_input}"
        ),
        expected_output="A helpful response addressing the user's request",
        agent=agent,
    )

    crew = Crew(agents=[agent], tasks=[task], verbose=False)
    result = crew.kickoff()
    response = str(result)

    conversation_context += f"Agent: {response}\n"
    print(f"Agent: {response}\n")
What's Happening:
  • Interactive CLI Setup: The code creates an infinite loop that continuously prompts for user input and maintains the entire conversation history in a string variable.
  • Input Validation: Empty inputs are ignored to prevent processing blank messages and keep the conversation clean.
  • Context Building: Each user message is appended to the conversation context, which preserves the full dialogue history for better agent responses.
  • Dynamic Task Creation: For every user input, a new Task is created that includes both the full conversation history and the current request as context.
  • Crew Execution: A Crew is instantiated with the agent and task, then kicked off to process the request and generate a response.
  • Response Management: The agent's response is converted to a string, added to the conversation context, and displayed to the user, maintaining conversational continuity.

Complete Code

Here's the complete code to get you started with Textit and CrewAI:

python
from crewai import Agent, Task, Crew, LLM
from crewai_tools import MCPServerAdapter
from composio import Composio
from dotenv import load_dotenv
import os

load_dotenv()

GOOGLE_API_KEY = os.getenv("GOOGLE_API_KEY")
COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY")
COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID")

if not GOOGLE_API_KEY:
    raise ValueError("GOOGLE_API_KEY is not set in the environment.")
if not COMPOSIO_API_KEY:
    raise ValueError("COMPOSIO_API_KEY is not set in the environment.")
if not COMPOSIO_USER_ID:
    raise ValueError("COMPOSIO_USER_ID is not set in the environment.")

# Initialize Composio and create a session
composio = Composio(api_key=COMPOSIO_API_KEY)
session = composio.create(
    user_id=COMPOSIO_USER_ID,
    toolkits=["textit"],
)
url = session.mcp.url

# Configure LLM
llm = LLM(
    model="gpt-5",
    api_key=os.getenv("OPENAI_API_KEY"),
)

server_params = {
    "url": url,
    "transport": "streamable-http",
    "headers": {"x-api-key": COMPOSIO_API_KEY},
}

with MCPServerAdapter(server_params) as tools:
    agent = Agent(
        role="Search Assistant",
        goal="Help users with internet searches",
        backstory="You are an expert assistant with access to Composio Search tools.",
        tools=tools,
        llm=llm,
        verbose=False,
        max_iter=10,
    )

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

    conversation_context = ""

    while True:
        user_input = input("You: ").strip()

        if user_input.lower() in ["exit", "quit", "bye"]:
            print("\nGoodbye!")
            break

        if not user_input:
            continue

        conversation_context += f"\nUser: {user_input}\n"
        print("\nAgent is thinking...\n")

        task = Task(
            description=(
                f"Conversation history:\n{conversation_context}\n\n"
                f"Current request: {user_input}"
            ),
            expected_output="A helpful response addressing the user's request",
            agent=agent,
        )

        crew = Crew(agents=[agent], tasks=[task], verbose=False)
        result = crew.kickoff()
        response = str(result)

        conversation_context += f"Agent: {response}\n"
        print(f"Agent: {response}\n")

Conclusion

You now have a CrewAI agent connected to Textit through Composio's Tool Router. The agent can perform Textit operations through natural language commands.

Next steps:

  • Add role-specific instructions to customize agent behavior
  • Plug in more toolkits for multi-app workflows
  • Chain tasks for complex multi-step operations
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

Retrieve a campaign by UUID, returning its UUID, name, archived status, group and creation time.

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

List TextIt broadcasts to review outgoing message activity, with optional request filters and pagination.

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

List workspace-level global variables, with cursor pagination.

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

Retrieve a page of messages with optional UUID, folder, contact, broadcast, or date-range filters.

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

Create and send a TextIt broadcast to selected URNs, contacts, or groups, using message translations.

Update Contact

Tool to update an existing contact.

FRAMEWORKS

How to build Textit MCP Agent with another framework

Claude Code logo

Claude Code

Use Textit MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Textit MCP with Claude Cowork

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Textit MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Textit MCP with Claude Agent SDK

Codex logo

Codex

Use Textit MCP with Codex

OpenClaw logo

OpenClaw

Use Textit MCP with OpenClaw

Hermes logo

Hermes

Use Textit MCP with Hermes

Atomic Agent logo

Atomic Agent

Use Textit MCP with Atomic Agent

Google ADK logo

Google ADK

Use Textit MCP with Google ADK

LangChain logo

LangChain

Use Textit MCP with LangChain

Vercel AI SDK logo

Vercel AI SDK

Use Textit MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Textit MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Textit MCP with LlamaIndex

Pydantic AI logo

Pydantic AI

Use Textit MCP with Pydantic AI

AutoGen logo

AutoGen

Use Textit MCP with AutoGen

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. CrewAI 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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