How to integrate Bannerbite MCP with Pydantic AI

This guide walks you through connecting Bannerbite to Pydantic AI using the Composio tool router. By the end, you'll have a working Bannerbite agent that can generate campaign images from saved templates, create product videos for new launches, render social banners for holiday sale through natural language commands. This guide will help you understand how to give your Pydantic AI agent real control over a Bannerbite account through Composio's Bannerbite MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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Bannerbite is a creative automation platform for generating images and videos from reusable projects and templates. It helps teams produce on-brand visual assets faster without rebuilding designs from scratch.

6 Tools

Introduction

This guide walks you through connecting Bannerbite to Pydantic AI using the Composio tool router. By the end, you'll have a working Bannerbite agent that can generate campaign images from saved templates, create product videos for new launches, render social banners for holiday sale through natural language commands.

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

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

Also integrate Bannerbite with

OpenAI Agents SDKClaude Agent SDKClaude CodeClaude CoworkCodexOpenClawHermesCLIGoogle ADKLangChainVercel AI SDKMastra AILlamaIndexCrewAI

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 Bannerbite
  • 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 Bannerbite 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 Bannerbite MCP server, and what's possible with it?

The Bannerbite MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Bannerbite account. It provides structured and secure access to your creative projects and reusable templates, so your agent can browse projects, inspect templates, review editable scene fields, and generate images, videos, or overlays on your behalf.

  • Project discovery: Have your agent list your Bannerbite projects and retrieve details about a specific creative project.
  • Template browsing: Let the agent find the reusable creative templates within a project and review their available output sizes.
  • Scene field review: Direct your agent to inspect the editable text, images, and other scene fields in a template before creating media.
  • Image and video generation: Instruct your agent to generate an image or video from a selected template using your chosen scene content.
  • Overlay creation: Have your agent create an overlay render from a reusable Bannerbite template for use in your creative workflow.

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 Bannerbite
  • 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 Bannerbite
  • MCPServerStreamableHTTP connects to the Bannerbite 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 Bannerbite
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["bannerbite"],
    )
    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 Bannerbite 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
bannerbite_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
agent = Agent(
    "openai:gpt-5",
    toolsets=[bannerbite_mcp],
    instructions=(
        "You are a Bannerbite assistant. Use Bannerbite tools to help users "
        "with their requests. Ask clarifying questions when needed."
    ),
)
What's happening:
  • The MCP client connects to the Bannerbite endpoint
  • The agent uses GPT-5 to interpret user commands and perform Bannerbite 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 Bannerbite.\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
  • Bannerbite 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 Bannerbite 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 Bannerbite
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["bannerbite"],
    )
    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
    bannerbite_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
    agent = Agent(
        "openai:gpt-5",
        toolsets=[bannerbite_mcp],
        instructions=(
            "You are a Bannerbite assistant. Use Bannerbite 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 Bannerbite.\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 Bannerbite through Composio's Tool Router. With this setup, your agent can perform real Bannerbite 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 + Bannerbite 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 Bannerbite action and event your agent gets out of the box.

Generate Media

Queue one asynchronous image, video, or overlay render from a Bannerbite bite.

Get Bite

Return one Bannerbite bite by its numeric bite ID, including template and output-size details; fail explicitly when the bite does not exist.

Get Project

Return one Bannerbite project by its numeric project ID; fail explicitly when the project does not exist.

Get Scene Data

Return the editable scene fields for a Bannerbite bite so their names and current values can be used in a render request.

List Bites

Return one provider page of Bannerbite bites in a project, up to 100 bites; the API exposes no verified way to request another page.

List Projects

Return one provider page of projects owned by the connected Bannerbite account, up to 100 projects; the API exposes no verified way to request another page.

FRAMEWORKS

How to build Bannerbite MCP Agent with another framework

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Bannerbite MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Bannerbite MCP with Claude Agent SDK

Claude Code logo

Claude Code

Use Bannerbite MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Bannerbite MCP with Claude Cowork

Codex logo

Codex

Use Bannerbite MCP with Codex

OpenClaw logo

OpenClaw

Use Bannerbite MCP with OpenClaw

Hermes logo

Hermes

Use Bannerbite MCP with Hermes

CLI logo

CLI

Use Bannerbite MCP with CLI

Google ADK logo

Google ADK

Use Bannerbite MCP with Google ADK

LangChain logo

LangChain

Use Bannerbite MCP with LangChain

Vercel AI SDK logo

Vercel AI SDK

Use Bannerbite MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Bannerbite MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Bannerbite MCP with LlamaIndex

CrewAI logo

CrewAI

Use Bannerbite MCP with CrewAI

FAQ

Frequently asked questions

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

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

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