# How to integrate Engage MCP with CrewAI

```json
{
  "title": "How to integrate Engage MCP with CrewAI",
  "toolkit": "Engage",
  "toolkit_slug": "engage",
  "framework": "CrewAI",
  "framework_slug": "crew-ai",
  "url": "https://composio.dev/toolkits/engage/framework/crew-ai",
  "markdown_url": "https://composio.dev/toolkits/engage/framework/crew-ai.md",
  "updated_at": "2026-03-29T06:32:23.042Z"
}
```

## Introduction

This guide walks you through connecting Engage to CrewAI using the Composio tool router. By the end, you'll have a working Engage agent that can send sms to users about black friday deals, create and schedule a new email campaign, get analytics on last week's push notifications through natural language commands.
This guide will help you understand how to give your CrewAI agent real control over a Engage account through Composio's Engage MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Engage with

- [OpenAI Agents SDK](https://composio.dev/toolkits/engage/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/engage/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/engage/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/engage/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/engage/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/engage/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/engage/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/engage/framework/cli)
- [Google ADK](https://composio.dev/toolkits/engage/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/engage/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/engage/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/engage/framework/mastra-ai)
- [LlamaIndex](https://composio.dev/toolkits/engage/framework/llama-index)

## TL;DR

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

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

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `ENGAGE_ADD_CUSTOMER_TO_ACCOUNTS` | Add Customer to Accounts | Tool to add a customer to one or more account entities. Use when you need to associate a user with accounts and optionally assign roles. |
| `ENGAGE_ADD_USER_TO_LISTS` | Add User to Lists | Tool to add a Customer or Account to one or more Lists in Engage.so. Use when you need to subscribe a user to specific lists for targeted messaging. |
| `ENGAGE_ARCHIVE_LIST` | Archive List | Tool to archive a List in Engage. Use when you want to prevent new subscribers from being added to a list. Existing subscribers will not be affected. |
| `ENGAGE_ARCHIVE_USER` | Archive User | Tool to archive a user in Engage. Use when you need to deactivate a user account while preserving all historical data. The user will stop being active and all engagement and events for the user will be stopped, but all messages, logs, and related data will be preserved. |
| `ENGAGE_CONVERT_USER_TYPE` | Convert User Type | Tool to convert a user between Customer and Account entity types. Use when you need to change a customer to an account or vice versa. |
| `ENGAGE_CREATE_LIST` | Create List | Tool to create a new List in Engage for organizing subscribers. Use when you need to set up a new list for managing contacts or subscribers. |
| `ENGAGE_CREATE_USER` | Create User | Tool to create a new user (Customer or Account) in Engage. Use when you need to add a user with optional metadata, device tokens, or list subscriptions. |
| `ENGAGE_DELETE_SUBSCRIBER_FROM_LIST` | Delete Subscriber From List | Tool to remove a subscriber from a List entirely (different from unsubscribing). Use when you need to completely delete a subscriber's association with a specific list. |
| `ENGAGE_DELETE_USER` | Delete User | Tool to completely delete all user data for a Customer or Account. This is a permanent, destructive action that removes all associated user data from Engage. |
| `ENGAGE_GET_ACCOUNT_MEMBERS` | Get Account Members | Tool to retrieve all members (Customers) of an Account in Engage. Use when you need to list users who are part of a specific account. |
| `ENGAGE_GET_LIST` | Get List | Tool to retrieve a single List by its ID. Use when you need to fetch details about a specific List. |
| `ENGAGE_GET_USER_BY_ID` | Get User By ID | Tool to retrieve a single user by their user ID. Use when you need to fetch complete user information including metadata, attributes, devices, lists, segments, and message statistics. |
| `ENGAGE_LIST_LISTS` | List Lists | Tool to retrieve a paginated list of all Lists in Engage. Use when you need to view available Lists or iterate through all Lists in the account. |
| `ENGAGE_LIST_USERS` | List Users | Tool to retrieve a paginated list of all users in Engage. Use when you need to list users with optional filtering by email and cursor-based pagination support. |
| `ENGAGE_MERGE_USERS` | Merge Users | Tool to merge two user profiles in Engage. The source user is merged into the destination user, and the source user profile is removed. Use when you need to consolidate duplicate user accounts or combine user data from multiple profiles into a single account. |
| `ENGAGE_REMOVE_CUSTOMER_FROM_ACCOUNT` | Remove Customer from Account | Tool to remove a Customer from an Account in Engage. Use when you need to disassociate a customer from a specific account. |
| `ENGAGE_BATCH_REQUEST` | Batch Request | Tool to batch multiple create user, update user, and add user events operations into a single API call. Use when you need to perform multiple operations efficiently at the cost of one API request. The batch is queued for processing without immediate validation, so ensure all parameters are correct. Request size must remain under 100KB. |
| `ENGAGE_SUBSCRIBE_USER_TO_LIST` | Subscribe User to List | Tool to create a user and subscribe them to an Engage.so List. Use when you need to add users to a specific list for email marketing or user segmentation. If the user already exists, they will be added to the List without creating a duplicate. |
| `ENGAGE_TRACK_USER_EVENT` | Track User Event | Tool to add user events to Engage. Use this to track user actions and events in your application. You can later segment users based on these actions or events. |
| `ENGAGE_UPDATE_ACCOUNT_ROLE` | Update Account Role | Tool to update the role of a Customer in an Account or set a new one if none exists. Use when you need to assign or change a customer's role within a specific account. |
| `ENGAGE_UPDATE_SUBSCRIBER_STATUS` | Update Subscriber Status | Tool to update a subscriber's status on a List. Use when you need to subscribe, re-subscribe, or unsubscribe a user from a specific List. |
| `ENGAGE_UPDATE_USER` | Update User | Tool to update user data and attributes on Engage. Use this to update user data changes like changes in plan, name, location, etc. If the user doesn't exist, this method creates the user. |

## Supported Triggers

None listed.

## Creating MCP Server - Stand-alone vs Composio SDK

The Engage MCP server is an implementation of the Model Context Protocol that connects your AI agent to Engage. It provides structured and secure access so your agent can perform Engage operations on your behalf through a secure, permission-based interface.
With Composio's managed implementation, you don't have to create your own developer app. For production, if you're building an end product, we recommend using your own credentials. The managed server helps you prototype fast and go from 0-1 faster.

## Step-by-step Guide

### 1. Prerequisites

Before starting, make sure you have:
- Python 3.9 or higher
- A Composio account and API key
- A Engage connection authorized in Composio
- An OpenAI API key for the CrewAI LLM
- Basic familiarity with Python

### 1. Getting API Keys for OpenAI and Composio

OpenAI API Key
- Go to the [OpenAI dashboard](https://platform.openai.com/settings/organization/api-keys) 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](https://dashboard.composio.dev?utm_source=toolkits&utm_medium=framework_docs).
- Navigate to your API settings and generate a new API key.
- Store this key securely as you'll need it for authentication.

### 2. Install dependencies

**What's happening:**
- composio connects your agent to Engage via MCP
- crewai provides Agent, Task, Crew, and LLM primitives
- crewai-tools[mcp] includes MCP helpers
- python-dotenv loads environment variables from .env
```bash
pip install composio crewai crewai-tools[mcp] python-dotenv
```

### 3. Set up environment variables

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
```bash
COMPOSIO_API_KEY=your_composio_api_key_here
USER_ID=your_user_id_here
OPENAI_API_KEY=your_openai_api_key_here
```

### 4. Import dependencies

**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 Engage MCP URL
```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")
```

### 5. Create a Composio Tool Router session for Engage

**What's happening:**
- You create a Engage only session through Composio
- Composio returns an MCP HTTP URL that exposes Engage tools
```python
composio_client = Composio(api_key=COMPOSIO_API_KEY)
session = composio_client.create(user_id=COMPOSIO_USER_ID, toolkits=["engage"])

url = session.mcp.url
```

### 6. Initialize the MCP Server

**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.
```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,
    )
```

### 7. Create a CLI Chatloop and define the Crew

**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.
```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")
```

## Complete Code

```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=["engage"],
)
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 Engage through Composio's Tool Router. The agent can perform Engage 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 Engage MCP Agent with another framework

- [OpenAI Agents SDK](https://composio.dev/toolkits/engage/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/engage/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/engage/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/engage/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/engage/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/engage/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/engage/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/engage/framework/cli)
- [Google ADK](https://composio.dev/toolkits/engage/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/engage/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/engage/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/engage/framework/mastra-ai)
- [LlamaIndex](https://composio.dev/toolkits/engage/framework/llama-index)

## Related Toolkits

- [Google Sheets](https://composio.dev/toolkits/googlesheets) - Google Sheets is a cloud-based spreadsheet tool for real-time collaboration and data analysis. It lets teams work together from anywhere, updating information instantly.
- [Notion](https://composio.dev/toolkits/notion) - Notion is a collaborative workspace for notes, docs, wikis, and tasks. It streamlines team knowledge, project tracking, and workflow customization in one place.
- [Airtable](https://composio.dev/toolkits/airtable) - Airtable combines the flexibility of spreadsheets with the power of a database for easy project and data management. Teams use Airtable to organize, track, and collaborate with custom views and automations.
- [Asana](https://composio.dev/toolkits/asana) - Asana is a collaborative work management platform for teams to organize and track projects. It streamlines teamwork, boosts productivity, and keeps everyone aligned on goals.
- [Google Tasks](https://composio.dev/toolkits/googletasks) - Google Tasks is a to-do list and task management tool integrated into Gmail and Google Calendar. It helps you organize, track, and complete tasks across your Google ecosystem.
- [Linear](https://composio.dev/toolkits/linear) - Linear is a modern issue tracking and project planning tool for fast-moving teams. It helps streamline workflows, organize projects, and boost productivity.
- [Jira](https://composio.dev/toolkits/jira) - Jira is Atlassian’s platform for bug tracking, issue tracking, and agile project management. It helps teams organize work, prioritize tasks, and deliver projects efficiently.
- [Clickup](https://composio.dev/toolkits/clickup) - ClickUp is an all-in-one productivity platform for managing tasks, docs, goals, and team collaboration. It streamlines project workflows so teams can work smarter and stay organized in one place.
- [Monday](https://composio.dev/toolkits/monday) - Monday.com is a customizable work management platform for project planning and collaboration. It helps teams organize tasks, automate workflows, and track progress in real time.
- [Reddit](https://composio.dev/toolkits/reddit) - Reddit is a social news platform with thriving user-driven communities (subreddits). It's the go-to place for discussion, content sharing, and viral marketing.
- [Facebook](https://composio.dev/toolkits/facebook) - Facebook is a social media and advertising platform for businesses and creators. It helps you connect, share, and manage content across your public Facebook Pages.
- [Linkedin](https://composio.dev/toolkits/linkedin) - LinkedIn is a professional networking platform for connecting, sharing content, and engaging with business opportunities. It's the go-to place for building your professional brand and unlocking new career connections.
- [Active campaign](https://composio.dev/toolkits/active_campaign) - ActiveCampaign is a marketing automation and CRM platform for managing email campaigns, sales pipelines, and customer segmentation. It helps businesses engage customers and drive growth through smart automation and targeted outreach.
- [ActiveTrail](https://composio.dev/toolkits/active_trail) - ActiveTrail is a user-friendly email marketing and automation platform. It helps you reach subscribers and automate campaigns with ease.
- [Addressfinder](https://composio.dev/toolkits/addressfinder) - Addressfinder is a data quality platform for verifying addresses, emails, and phone numbers. It helps you ensure accurate customer and contact data every time.
- [Agiled](https://composio.dev/toolkits/agiled) - Agiled is an all-in-one business management platform for CRM, projects, and finance. It helps you streamline workflows, consolidate client data, and manage business processes in one place.
- [Ahrefs](https://composio.dev/toolkits/ahrefs) - Ahrefs is an SEO and marketing platform for site audits, keyword research, and competitor insights. It helps you improve search rankings and drive organic traffic.
- [Amcards](https://composio.dev/toolkits/amcards) - AMCards lets you create and mail personalized greeting cards online. Build stronger customer relationships with easy, automated card campaigns.
- [Ascora](https://composio.dev/toolkits/ascora) - Ascora is a cloud-based field service management platform for service businesses. It streamlines scheduling, invoicing, and customer operations in one place.
- [Basecamp](https://composio.dev/toolkits/basecamp) - Basecamp is a project management and team collaboration tool by 37signals. It helps teams organize tasks, share files, and communicate efficiently in one place.

## Frequently Asked Questions

### What are the differences in Tool Router MCP and Engage MCP?

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

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

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

---
[See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)
