How to integrate Unisender MCP with CrewAI

GET STARTED FOR FREE
Framework Integration Gradient
Unisender Logo
CrewAI Logo
divider

Introduction

This guide walks you through connecting Unisender to CrewAI using the Composio tool router. By the end, you'll have a working Unisender agent that can send an sms campaign to new signups, create a new email list segment, check status of yesterday's email campaign through natural language commands.

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

The Unisender MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Unisender account. It provides structured and secure access so your agent can perform Unisender operations on your behalf.

Supported Tools & Triggers

Tools
Check Email StatusTool to check the delivery status of emails sent via sendEmail method.
Create Email TemplateTool to create a new email template for mass campaigns in UniSender.
Create FieldTool to create a new custom field for contact data in UniSender.
Create ListTool to create a new contact list for organizing thematic email campaigns in UniSender.
Create Subscriber NoteTool to create a note for a subscriber contact in UniSender.
Delete FieldTool to remove a custom field from the Unisender system.
Delete ListTool to permanently delete a contact list from your UniSender account.
Delete Subscriber NoteTool to delete a subscriber note from UniSender by its ID.
Delete TagTool to delete a tag by its ID and remove it from all associated contacts.
Delete TemplateTool to remove a template from the UniSender account.
Exclude Contact from ListsTool to remove contacts from specified lists or all lists in UniSender.
Export ContactsTool to export contact data from UniSender lists for synchronization.
Get CampaignsTool to retrieve list of campaigns from Unisender within a specified date range.
Get Campaign StatusTool to check the current status of a campaign in UniSender.
Get ContactTool to get information about a single contact from UniSender.
Get Contact Field ValuesTool to retrieve custom field values for a specific contact identified by email address.
Get FieldsTool to retrieve all custom user-defined fields for contact personalization and data management.
Get ListsTool to retrieve all existing mailing lists associated with the account.
Get MessagesTool to retrieve list of all messages with body and attachments.
Get Sender Domain ListTool to retrieve information about sender domains and their DKIM status.
Get TagsTool to retrieve all custom tags/labels for contact segmentation.
Get TemplateTool to retrieve detailed information about a specific email template by its ID.
Get TemplatesTool to retrieve list of all templates with full content including body.
Import Contacts (Bulk)Tool to bulk import contacts to UniSender with maximum 500 contacts per call.
Check if Contact is in ListsTool to check if a contact exists in specified mailing lists based on and/or conditions.
List MessagesTool to list all messages without body and attachments.
List TemplatesTool to list email templates without body content.
Subscribe Contact to ListsTool to add contacts to one or multiple mailing lists with optional tags and field values.
Unsubscribe ContactTool to unsubscribe contacts from mailing lists in UniSender.
Update Email TemplateTool to update an existing email template for mass campaigns.
Update FieldTool to modify parameters of an existing custom field in UniSender.
Update ListTool to update the parameters of an existing contact list in UniSender.
Update Subscriber NoteTool to update the content of an existing subscriber note in UniSender.

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 Unisender 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 Unisender 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 Unisender MCP URL

Create a Composio Tool Router session for Unisender

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

url = session.mcp.url
What's happening:
  • You create a Unisender only session through Composio
  • Composio returns an MCP HTTP URL that exposes Unisender 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 Unisender 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=["unisender"],
)
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 Unisender through Composio's Tool Router. The agent can perform Unisender 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 Unisender MCP Agent with another framework

OpenAI Agents SDK

OpenAI Agents SDK

Use Unisender MCP with OpenAI Agents SDK

Claude Agent SDK

Claude Agent SDK

Use Unisender MCP with Claude Agent SDK

Google ADK

Google ADK

Use Unisender MCP with Google ADK

LangChain

LangChain

Use Unisender MCP with LangChain

Vercel AI SDK

Vercel AI SDK

Use Unisender MCP with Vercel AI SDK

Mastra AI

Mastra AI

Use Unisender MCP with Mastra AI

LlamaIndex

LlamaIndex

Use Unisender MCP with LlamaIndex

Claude Code

Claude Code

Use Unisender MCP with Claude Code

Codex

Codex

Use Unisender MCP with Codex

FAQ

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

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

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

Yes, absolutely. You can configure which Unisender 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 Unisender 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.

Book a call↗Get started for free