How to integrate Botbaba MCP with CrewAI

Trusted by
AWS
Glean
Zoom
Airtable
GET STARTED FOR FREEGET A DEMO

30 min · no commitment · see it on your stack

Botbaba logo
CrewAI logo
divider

Introduction

This guide walks you through connecting Botbaba to CrewAI using the Composio tool router. By the end, you'll have a working Botbaba agent that can deploy new chatbot to whatsapp channel, update chatbot greeting message instantly, fetch conversation logs for last 24 hours through natural language commands.

This guide will help you understand how to give your CrewAI agent real control over a Botbaba account through Composio's Botbaba MCP server.

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

Also integrate Botbaba with

TL;DR

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

The Botbaba MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Botbaba account. It provides structured and secure access to your chatbot management platform, so your agent can perform actions like creating bots, updating conversation flows, managing integrations, deploying changes, and monitoring chatbot analytics on your behalf.

  • Bot creation and configuration: Instantly create new chatbots, set up welcome messages, and configure basic settings directly from your agent.
  • Conversational flow management: Update, organize, or refine conversation trees, intents, and responses for smarter, more natural chatbot interactions.
  • Integration with messaging platforms: Enable your agent to connect bots with channels like WhatsApp, Facebook Messenger, and web chat for seamless communication.
  • Real-time deployment and publishing: Push bot changes live or roll back updates—ensuring your chatbots stay current and relevant with minimal effort.
  • Analytics and performance monitoring: Automatically fetch usage statistics, analyze user engagement, and monitor bot performance to optimize conversational experiences.

Supported Tools & Triggers

Tools
Shopify Cart Creation SimulatorTool to simulate a Shopify cart creation webhook payload.
Cart Creation Shopify WebhookTool to receive Shopify Cart Creation webhooks.
Cart Update Shopify WebhookTool to forward Shopify cart update events to BotBaba.
Shopify Checkout Creation Webhook ReceiverTool to receive Shopify checkout creation webhook events.
Checkout Update Shopify WebhookTool to forward Shopify checkout/update events to Botbaba.
Delete a broadcast campaignTool to delete a broadcast campaign.
Delete ContactTool to delete a contact.
Delete a conversation flowTool to delete a conversation flow.
Delete TagTool to delete a tag.
Delete TemplateTool to delete a message template.
Delete a webhook subscriptionTool to delete a webhook subscription.
Execute Bot ActionTool to execute a bot action or workflow.
Execute Bot Action By UserTool to execute a bot action for specific users.
Get Bot Widget SettingsTool to retrieve widget configuration settings for a bot.
Get BroadcastTool to retrieve details of a specific broadcast.
Get BotBaba ContactTool to fetch a BotBaba contact by its ID.
Get Contact AnalyticsTool to retrieve analytics data for contacts.
Get Filename from PathTool to extract the filename from a file path.
Get FlowTool to retrieve details of a specific flow.
Get MessageTool to retrieve status of a specific message.
Get Message AnalyticsTool to retrieve analytics data for a specific message.
Get TemplateTool to retrieve details of a specific template.
Get WebhookTool to retrieve details of a specific webhook.
List BroadcastsTool to list all broadcast campaigns.
List FlowsTool to list all conversation flows with their IDs and metadata.
List TagsTool to list all tags.
List TemplatesTool to retrieve a paginated list of templates.
List Webhook Event TypesTool to list available webhook event types.
List WebhooksTool to list all registered webhooks.
Receive Shopify Order Cancellation WebhookTool to receive Shopify order cancellation webhooks.
Order Fulfillment SimulatorTool to simulate a Shopify order fulfillment webhook payload.
Order Fulfillment Shopify WebhookTool to receive Shopify Order Fulfillment webhooks.
Order Payment Shopify WebhookTool to receive Shopify Order Payment webhooks.
Send WhatsApp Template MessageTool to forward/send a WhatsApp template message via Botbaba.
Shopify Checkout Creation SimulatorTool to simulate a Shopify checkout creation webhook payload.
Shopify Checkout Update SimulatorTool to simulate a Shopify checkout update webhook payload.
Update ContactTool to update an existing contact.
Update TagTool to update an existing tag.
Update TemplateTool to update an existing message template.
Update WebhookTool to update an existing webhook.
Gupshup WhatsApp Webhook Event SimulatorTool to simulate Gupshup WhatsApp webhook events.
Forward Gupshup Webhook MessageTool to forward inbound WhatsApp webhook events from Gupshup to Botbaba.

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

Prerequisites

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

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.

Install dependencies

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

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

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 Botbaba MCP URL

Create a Composio Tool Router session for Botbaba

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

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

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.

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 Botbaba 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=["botbaba"],
)
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 Botbaba through Composio's Tool Router. The agent can perform Botbaba 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

How to build Botbaba MCP Agent with another framework

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Botbaba MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Botbaba MCP with Claude Agent SDK

Claude Code logo

Claude Code

Use Botbaba MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Botbaba MCP with Claude Cowork

Codex logo

Codex

Use Botbaba MCP with Codex

OpenClaw logo

OpenClaw

Use Botbaba MCP with OpenClaw

Hermes logo

Hermes

Use Botbaba MCP with Hermes

CLI logo

CLI

Use Botbaba MCP with CLI

Google ADK logo

Google ADK

Use Botbaba MCP with Google ADK

LangChain logo

LangChain

Use Botbaba MCP with LangChain

Vercel AI SDK logo

Vercel AI SDK

Use Botbaba MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Botbaba MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Botbaba MCP with LlamaIndex

FAQ

What are the differences in Tool Router MCP and Botbaba MCP?

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

Can I use Tool Router MCP with CrewAI?

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 Botbaba tools.

Can I manage the permissions and scopes for Botbaba while using Tool Router?

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

Used by agents from

Context
Letta
glean
HubSpot
Agent.ai
Altera
DataStax
Entelligence
Rolai
Context
Letta
glean
HubSpot
Agent.ai
Altera
DataStax
Entelligence
Rolai
Context
Letta
glean
HubSpot
Agent.ai
Altera
DataStax
Entelligence
Rolai

Never worry about agent reliability

We handle tool reliability, observability, and security so you never have to second-guess an agent action.

Get started for freeGet a demo↗