How to integrate Brevo MCP with CrewAI

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Introduction

This guide walks you through connecting Brevo to CrewAI using the Composio tool router. By the end, you'll have a working Brevo agent that can send sms campaign to new subscribers, create or update an email template, find contact details by email address, delete inactive email template by id through natural language commands.

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

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

TL;DR

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

The Brevo MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Brevo account. It provides structured and secure access to your email, SMS marketing, automation, and contact management tools, so your agent can perform actions like sending campaigns, managing contacts, creating templates, and retrieving account details on your behalf.

  • Automated campaign management: Let your agent create, schedule, or delete SMS campaigns, including customizing recipients, sender details, and campaign content.
  • Contact and company management: Easily add new contacts or companies, update existing records, or remove outdated ones to keep your database organized and up to date.
  • Email template automation: Empower your agent to create, update, or delete email templates for consistent and efficient campaign design and execution.
  • Account information retrieval: Ask your agent to fetch detailed account information, including plan details, credits, and profile data, for easy monitoring and reporting.
  • Contact search and segmentation: Have your agent search for specific contacts or retrieve segmented contact lists based on filters like creation date, list IDs, or attributes.

Supported Tools & Triggers

Tools
Create a companyThis tool allows you to create a new company in your brevo account.
Create or Update Email TemplateThis tool creates a new email template or updates an existing one in brevo.
Create SMS CampaignThis tool allows you to create a new sms campaign in brevo.
Delete a companyDeletes a company from brevo using its unique identifier.
Delete ContactDeletes a contact from brevo using its unique identifier.
Delete Email TemplateThis tool deletes an inactive email template from brevo.
Delete SMS CampaignThis tool deletes an existing sms campaign.
Find ContactThis tool checks if a contact exists in brevo.
Get Account InformationThis tool retrieves information about the brevo account, including account holder's email, first name, last name, company name, and address, as well as details about the current plan such as type, credits, start date, and end date.
Get all contactsThis tool retrieves all contacts from your brevo account.
Get all email templatesThis tool retrieves a list of all email templates created in your brevo account.
Get All SendersThis tool retrieves a list of all senders associated with the brevo account.
Get Company DetailsThis tool retrieves the details of a specific company by its unique id.
Get Contact DetailsThis tool retrieves detailed information about a specific contact in brevo.
Get SMS Campaign DetailsRetrieves the details of a specific sms campaign.
Get SMS CampaignsThis tool retrieves a list of all sms campaigns created in brevo.
List All CompaniesThis action retrieves a list of all companies stored in the brevo crm.
List Email CampaignsThis tool retrieves a list of all email campaigns associated with the user's brevo account.
Update Email CampaignUpdates an email campaign in brevo using its unique identifier.

What is the Composio tool router, and how does it fit here?

What is Tool Router?

Composio's Tool Router 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 Tool Router

The tool router generates a secure MCP URL that your agents can access to perform actions.

How the Tool Router works

The Tool Router 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 Brevo 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 python-dotenv
What's happening:
  • composio connects your agent to Brevo via MCP
  • crewai provides Agent, Task, Crew, and LLM primitives
  • crewai-tools 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
from crewai import Agent, Task, Crew, LLM
from crewai_tools import MCPServerAdapter  # optional import if you plan to adapt tools
from composio import Composio
from dotenv import load_dotenv
import os
from crewai.mcp import MCPServerHTTP

load_dotenv()
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 Brevo MCP URL

Create a Composio Tool Router session for Brevo

python
composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
session = composio.create(
    user_id=os.getenv("USER_ID"),
    toolkits=["brevo"],
)
url = session.mcp.url
What's happening:
  • You create a Brevo only session through Composio
  • Composio returns an MCP HTTP URL that exposes Brevo tools

Configure the LLM

python
llm = LLM(
    model="gpt-5-mini",
    api_key=os.getenv("OPENAI_API_KEY"),
)
What's happening:
  • CrewAI will call this LLM for planning and responses
  • You can swap in a different model if needed

Attach the MCP server and create the agent

python
toolkit_agent = Agent(
    role="Brevo Assistant",
    goal="Help users interact with Brevo through natural language commands",
    backstory=(
        "You are an expert assistant with access to Brevo tools. "
        "You can perform various Brevo operations on behalf of the user."
    ),
    mcps=[
        MCPServerHTTP(
            url=url,
            streamable=True,
            cache_tools_list=True,
            headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")},
        ),
    ],
    llm=llm,
    verbose=True,
    max_iter=10,
)
What's happening:
  • MCPServerHTTP connects the agent to the Brevo MCP endpoint
  • cache_tools_list saves a tools catalog for faster subsequent runs
  • verbose helps you see what the agent is doing

Add a REPL loop with Task and Crew

python
print("Chat started! Type 'exit' or 'quit' to end.\n")
print("Try asking the agent to perform Brevo operations.\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"Based on the conversation history:\n{conversation_context}\n\n"
            f"Current user request: {user_input}\n\n"
            f"Please help the user with their Brevo related request."
        ),
        expected_output="A helpful response addressing the user's request",
        agent=toolkit_agent,
    )

    crew = Crew(
        agents=[toolkit_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:
  • You build a simple chat loop and keep a running context
  • Each user turn becomes a Task handled by the same agent
  • Crew executes the task and returns a response

Run the application

python
if __name__ == "__main__":
    main()
What's happening:
  • Standard Python entry point so you can run python crewai_brevo_agent.py

Complete Code

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

python
# file: crewai_brevo_agent.py
from crewai import Agent, Task, Crew, LLM
from crewai_tools import MCPServerAdapter  # optional
from composio import Composio
from dotenv import load_dotenv
import os
from crewai.mcp import MCPServerHTTP

load_dotenv()

def main():
    # Initialize Composio and create a Brevo session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["brevo"],
    )
    url = session.mcp.url

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

    # Create Brevo assistant agent
    toolkit_agent = Agent(
        role="Brevo Assistant",
        goal="Help users interact with Brevo through natural language commands",
        backstory=(
            "You are an expert assistant with access to Brevo tools. "
            "You can perform various Brevo operations on behalf of the user."
        ),
        mcps=[
            MCPServerHTTP(
                url=url,
                streamable=True,
                cache_tools_list=True,
                headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")},
            ),
        ],
        llm=llm,
        verbose=True,
        max_iter=10,
    )

    print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
    print("Try asking the agent to perform Brevo operations.\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"Based on the conversation history:\n{conversation_context}\n\n"
                f"Current user request: {user_input}\n\n"
                f"Please help the user with their Brevo related request."
            ),
            expected_output="A helpful response addressing the user's request",
            agent=toolkit_agent,
        )

        crew = Crew(
            agents=[toolkit_agent],
            tasks=[task],
            verbose=False,
        )

        result = crew.kickoff()
        response = str(result)

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

if __name__ == "__main__":
    main()

Conclusion

You now have a CrewAI agent connected to Brevo through Composio's Tool Router. The agent can perform Brevo 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 Brevo MCP Agent with another framework

FAQ

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

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

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

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

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