How to integrate Bannerbear MCP with CrewAI

This guide walks you through connecting Bannerbear to CrewAI using the Composio tool router. By the end, you'll have a working Bannerbear agent that can merge multiple marketing pdfs into one file, list all video assets created this week, get available fonts for instagram templates through natural language commands. This guide will help you understand how to give your CrewAI agent real control over a Bannerbear account through Composio's Bannerbear MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

Bannerbear logoBannerbear
Api Key

Bannerbear is an API-driven platform for generating images and videos automatically at scale. It helps businesses create custom graphics, social visuals, and marketing assets using powerful templates.

33 Tools

Introduction

This guide walks you through connecting Bannerbear to CrewAI using the Composio tool router. By the end, you'll have a working Bannerbear agent that can merge multiple marketing pdfs into one file, list all video assets created this week, get available fonts for instagram templates through natural language commands.

This guide will help you understand how to give your CrewAI agent real control over a Bannerbear account through Composio's Bannerbear 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:
  • Get a Composio API key and configure your Bannerbear connection
  • Set up CrewAI with an MCP enabled agent
  • Create a Tool Router session or standalone MCP server for Bannerbear
  • Build a conversational loop where your agent can execute Bannerbear 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 Bannerbear MCP server, and what's possible with it?

The Bannerbear MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Bannerbear account. It provides structured and secure access to your Bannerbear workspace, so your agent can generate images, create videos, manage templates, merge PDFs, and retrieve creative assets on your behalf.

  • Automated image and video generation: Enable your agent to create customized graphics or videos at scale using your Bannerbear templates and project assets.
  • Template browsing and management: Let your agent list, inspect, and select templates or template sets for creative projects, making it easy to automate content workflows.
  • Font and asset discovery: Have your agent retrieve available fonts and signed bases, ensuring the right design elements are used for every creative output.
  • PDF merging automation: Direct your agent to combine multiple PDFs into a single document, streamlining report or collateral creation.
  • Account and usage monitoring: Allow your agent to fetch current account status, API usage, and quota information to keep your creative operations running smoothly.

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 Bannerbear 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 Bannerbear 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 Bannerbear MCP URL
6

Create a Composio Tool Router session for Bannerbear

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

url = session.mcp.url
What's happening:
  • You create a Bannerbear only session through Composio
  • Composio returns an MCP HTTP URL that exposes Bannerbear 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 Bannerbear 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=["bannerbear"],
)
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 Bannerbear through Composio's Tool Router. The agent can perform Bannerbear 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 Bannerbear action and event your agent gets out of the box.

Create Project

Creates a new Bannerbear project with the specified name and optional settings.

Create Signed Base

Tool to create a signed URL base for a template.

Create Template

Create a new blank template in a Bannerbear project.

Create Template Set

Tool to create a new template set by grouping multiple templates together.

Create Video Template

Tool to create a new video template for video generation in Bannerbear.

Create Webhook

Create a project-level webhook that fires for all events of a specific type.

Delete Template

Tool to delete a template referenced by its unique ID.

Delete Webhook

Tool to delete a webhook referenced by its unique ID.

Get Account Info

Retrieves Bannerbear account information including subscription plan, API usage, and quota limits.

Get Animated GIF

Tool to retrieve a single Animated Gif object by its unique identifier (UID).

Get Auth Status

Verify API authentication and check which project the API key is scoped to.

Get Available Fonts

This tool retrieves a list of all available fonts in Bannerbear.

Get Image

Retrieves a single Image object by its unique identifier (UID).

Get Project

Retrieves detailed information about a specific Bannerbear project by its unique identifier (UID).

Get Screenshot

Retrieve a single Screenshot object referenced by its unique ID.

Get Signed Bases

This tool retrieves a list of signed bases for a specific template.

Get Template

Tool to retrieve a single template by its unique ID with layer defaults.

Get Template Set Details

This tool retrieves detailed information about a specific template set using its unique identifier (UID).

Get Webhook

Retrieves a single Webhook object by its unique ID.

Hydrate Project

Hydrate a project by copying templates from another project.

Import Template

Tool to import templates from the Bannerbear template library or from other projects.

Join PDFs

Merges multiple PDF files into a single combined PDF document.

List Animated GIFs

Lists all animated GIFs in a Bannerbear project.

List Collections

Lists all collections in a Bannerbear project.

List Effects

Tool to list all available image effects in Bannerbear.

List Images

Lists all images in a Bannerbear project.

List Projects

Lists all projects in a Bannerbear account.

List Screenshots

Lists all screenshots in a Bannerbear project.

List Templates

This action retrieves a list of all templates available in your Bannerbear project.

List Template Sets

Tool to list all template sets inside a project with pagination support.

List Videos

This action retrieves a list of all videos created in your Bannerbear account.

List Video Templates

This action retrieves a list of all video templates available in your Bannerbear project.

Update Template Set

Tool to update a template set by modifying its list of templates.

FAQ

Frequently asked questions

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

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

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