How to integrate Botbaba MCP with Pydantic AI

This guide walks you through connecting Botbaba to Pydantic AI 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 Pydantic AI 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.

Botbaba logoBotbaba
Api Key

Botbaba is a platform for building, managing, and deploying conversational AI chatbots across messaging channels. It streamlines chatbot automation, making it easier to integrate AI into customer interactions.

42 Tools

Introduction

This guide walks you through connecting Botbaba to Pydantic AI 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 Pydantic AI 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.

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TL;DR

Here's what you'll learn:
  • How to set up your Composio API key and User ID
  • How to create a Composio Tool Router session for Botbaba
  • How to attach an MCP Server to a Pydantic AI agent
  • How to stream responses and maintain chat history
  • How to build a simple REPL-style chat interface to test your Botbaba workflows

What is Pydantic AI?

Pydantic AI is a Python framework for building AI agents with strong typing and validation. It leverages Pydantic's data validation capabilities to create robust, type-safe AI applications.

Key features include:

  • Type Safety: Built on Pydantic for automatic data validation
  • MCP Support: Native support for Model Context Protocol servers
  • Streaming: Built-in support for streaming responses
  • Async First: Designed for async/await patterns

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.

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:
  • Python 3.9 or higher
  • A Composio account with an active API key
  • Basic familiarity with Python and async programming
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 pydantic-ai python-dotenv

Install the required libraries.

What's happening:

  • composio connects your agent to external SaaS tools like Botbaba
  • pydantic-ai lets you create structured AI agents with tool support
  • python-dotenv loads your environment variables securely from a .env file
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

Create a .env file in your project root.

What's happening:

  • COMPOSIO_API_KEY authenticates your agent to Composio's API
  • USER_ID associates your session with your account for secure tool access
  • OPENAI_API_KEY to access OpenAI LLMs
5

Import dependencies

python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerStreamableHTTP

load_dotenv()
What's happening:
  • We load environment variables and import required modules
  • Composio manages connections to Botbaba
  • MCPServerStreamableHTTP connects to the Botbaba MCP server endpoint
  • Agent from Pydantic AI lets you define and run the AI assistant
6

Create a Tool Router Session

python
async def main():
    api_key = os.getenv("COMPOSIO_API_KEY")
    user_id = os.getenv("USER_ID")
    if not api_key or not user_id:
        raise RuntimeError("Set COMPOSIO_API_KEY and USER_ID in your environment")

    # Create a Composio Tool Router session for Botbaba
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["botbaba"],
    )
    url = session.mcp.url
    if not url:
        raise ValueError("Composio session did not return an MCP URL")
What's happening:
  • We're creating a Tool Router session that gives your agent access to Botbaba tools
  • The create method takes the user ID and specifies which toolkits should be available
  • The returned session.mcp.url is the MCP server URL that your agent will use
7

Initialize the Pydantic AI Agent

python
# Attach the MCP server to a Pydantic AI Agent
botbaba_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
agent = Agent(
    "openai:gpt-5",
    toolsets=[botbaba_mcp],
    instructions=(
        "You are a Botbaba assistant. Use Botbaba tools to help users "
        "with their requests. Ask clarifying questions when needed."
    ),
)
What's happening:
  • The MCP client connects to the Botbaba endpoint
  • The agent uses GPT-5 to interpret user commands and perform Botbaba operations
  • The instructions field defines the agent's role and behavior
8

Build the chat interface

python
# Simple REPL with message history
history = []
print("Chat started! Type 'exit' or 'quit' to end.\n")
print("Try asking the agent to help you with Botbaba.\n")

while True:
    user_input = input("You: ").strip()
    if user_input.lower() in {"exit", "quit", "bye"}:
        print("\nGoodbye!")
        break
    if not user_input:
        continue

    print("\nAgent is thinking...\n", flush=True)

    async with agent.run_stream(user_input, message_history=history) as stream_result:
        collected_text = ""
        async for chunk in stream_result.stream_output():
            text_piece = None
            if isinstance(chunk, str):
                text_piece = chunk
            elif hasattr(chunk, "delta") and isinstance(chunk.delta, str):
                text_piece = chunk.delta
            elif hasattr(chunk, "text"):
                text_piece = chunk.text
            if text_piece:
                collected_text += text_piece
        result = stream_result

    print(f"Agent: {collected_text}\n")
    history = result.all_messages()
What's happening:
  • The agent reads input from the terminal and streams its response
  • Botbaba API calls happen automatically under the hood
  • The model keeps conversation history to maintain context across turns
9

Run the application

python
if __name__ == "__main__":
    asyncio.run(main())
What's happening:
  • The asyncio loop launches the agent and keeps it running until you exit

Complete Code

Here's the complete code to get you started with Botbaba and Pydantic AI:

python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerStreamableHTTP

load_dotenv()

async def main():
    api_key = os.getenv("COMPOSIO_API_KEY")
    user_id = os.getenv("USER_ID")
    if not api_key or not user_id:
        raise RuntimeError("Set COMPOSIO_API_KEY and USER_ID in your environment")

    # Create a Composio Tool Router session for Botbaba
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["botbaba"],
    )
    url = session.mcp.url
    if not url:
        raise ValueError("Composio session did not return an MCP URL")

    # Attach the MCP server to a Pydantic AI Agent
    botbaba_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
    agent = Agent(
        "openai:gpt-5",
        toolsets=[botbaba_mcp],
        instructions=(
            "You are a Botbaba assistant. Use Botbaba tools to help users "
            "with their requests. Ask clarifying questions when needed."
        ),
    )

    # Simple REPL with message history
    history = []
    print("Chat started! Type 'exit' or 'quit' to end.\n")
    print("Try asking the agent to help you with Botbaba.\n")

    while True:
        user_input = input("You: ").strip()
        if user_input.lower() in {"exit", "quit", "bye"}:
            print("\nGoodbye!")
            break
        if not user_input:
            continue

        print("\nAgent is thinking...\n", flush=True)

        async with agent.run_stream(user_input, message_history=history) as stream_result:
            collected_text = ""
            async for chunk in stream_result.stream_output():
                text_piece = None
                if isinstance(chunk, str):
                    text_piece = chunk
                elif hasattr(chunk, "delta") and isinstance(chunk.delta, str):
                    text_piece = chunk.delta
                elif hasattr(chunk, "text"):
                    text_piece = chunk.text
                if text_piece:
                    collected_text += text_piece
            result = stream_result

        print(f"Agent: {collected_text}\n")
        history = result.all_messages()

if __name__ == "__main__":
    asyncio.run(main())

Conclusion

You've built a Pydantic AI agent that can interact with Botbaba through Composio's Tool Router. With this setup, your agent can perform real Botbaba actions through natural language. You can extend this further by:
  • Adding other toolkits like Gmail, HubSpot, or Salesforce
  • Building a web-based chat interface around this agent
  • Using multiple MCP endpoints to enable cross-app workflows (for example, Gmail + Botbaba for workflow automation)
This architecture makes your AI agent "agent-native", able to securely use APIs in a unified, composable way without custom integrations.
TOOLS

Supported Tools

Every Botbaba action and event your agent gets out of the box.

Shopify Cart Creation Simulator

Tool to simulate a Shopify cart creation webhook payload.

Cart Creation Shopify Webhook

Tool to receive Shopify Cart Creation webhooks.

Cart Update Shopify Webhook

Tool to forward Shopify cart update events to BotBaba.

Shopify Checkout Creation Webhook Receiver

Tool to receive Shopify checkout creation webhook events.

Checkout Update Shopify Webhook

Tool to forward Shopify checkout/update events to Botbaba.

Delete a broadcast campaign

Tool to delete a broadcast campaign.

Delete Contact

Tool to delete a contact.

Delete a conversation flow

Tool to delete a conversation flow.

Delete Tag

Tool to delete a tag.

Delete Template

Tool to delete a message template.

Delete a webhook subscription

Tool to delete a webhook subscription.

Execute Bot Action

Tool to execute a bot action or workflow.

Execute Bot Action By User

Tool to execute a bot action for specific users.

Get Bot Widget Settings

Tool to retrieve widget configuration settings for a bot.

Get Broadcast

Tool to retrieve details of a specific broadcast.

Get BotBaba Contact

Tool to fetch a BotBaba contact by its ID.

Get Contact Analytics

Tool to retrieve analytics data for contacts.

Get Filename from Path

Tool to extract the filename from a file path.

Get Flow

Tool to retrieve details of a specific flow.

Get Message

Tool to retrieve status of a specific message.

Get Message Analytics

Tool to retrieve analytics data for a specific message.

Get Template

Tool to retrieve details of a specific template.

Get Webhook

Tool to retrieve details of a specific webhook.

List Broadcasts

Tool to list all broadcast campaigns.

List Flows

Tool to list all conversation flows with their IDs and metadata.

List Tags

Tool to list all tags.

List Templates

Tool to retrieve a paginated list of templates.

List Webhook Event Types

Tool to list available webhook event types.

List Webhooks

Tool to list all registered webhooks.

Receive Shopify Order Cancellation Webhook

Tool to receive Shopify order cancellation webhooks.

Order Fulfillment Simulator

Tool to simulate a Shopify order fulfillment webhook payload.

Order Fulfillment Shopify Webhook

Tool to receive Shopify Order Fulfillment webhooks.

Order Payment Shopify Webhook

Tool to receive Shopify Order Payment webhooks.

Send WhatsApp Template Message

Tool to forward/send a WhatsApp template message via Botbaba.

Shopify Checkout Creation Simulator

Tool to simulate a Shopify checkout creation webhook payload.

Shopify Checkout Update Simulator

Tool to simulate a Shopify checkout update webhook payload.

Update Contact

Tool to update an existing contact.

Update Tag

Tool to update an existing tag.

Update Template

Tool to update an existing message template.

Update Webhook

Tool to update an existing webhook.

Gupshup WhatsApp Webhook Event Simulator

Tool to simulate Gupshup WhatsApp webhook events.

Forward Gupshup Webhook Message

Tool to forward inbound WhatsApp webhook events from Gupshup to Botbaba.

FAQ

Frequently asked questions

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.

Yes, you can. Pydantic 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 Botbaba tools.

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.

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.

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