# How to integrate Remarkety MCP with CrewAI

```json
{
  "title": "How to integrate Remarkety MCP with CrewAI",
  "toolkit": "Remarkety",
  "toolkit_slug": "remarkety",
  "framework": "CrewAI",
  "framework_slug": "crew-ai",
  "url": "https://composio.dev/toolkits/remarkety/framework/crew-ai",
  "markdown_url": "https://composio.dev/toolkits/remarkety/framework/crew-ai.md",
  "updated_at": "2026-05-12T10:23:39.704Z"
}
```

## Introduction

This guide walks you through connecting Remarkety to CrewAI using the Composio tool router. By the end, you'll have a working Remarkety agent that can list all active email campaigns this week, fetch recent customers who abandoned carts, upload a new batch of newsletter contacts through natural language commands.
This guide will help you understand how to give your CrewAI agent real control over a Remarkety account through Composio's Remarkety MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Remarkety with

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

## TL;DR

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

The Remarkety MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Remarkety account. It provides structured and secure access to your marketing automation data, so your agent can manage campaigns, sync customer lists, track cart events, and update contacts on your behalf.
- Campaign management and insights: Retrieve and review detailed lists of your marketing campaigns, making it easy to analyze performance or schedule new sends.
- Customer data access: Fetch paginated customer lists from your Remarkety store, enabling targeted outreach or audience segmentation for your campaigns.
- Product catalog retrieval: Let your agent pull product details from your store, perfect for creating personalized marketing messages or promotions.
- Cart tracking for remarketing: Automatically sync customer cart updates to trigger remarketing flows and recover abandoned carts with personalized offers.
- Bulk contact import and sync: Upload or update large batches of contacts at once, keeping your lists current and campaigns reaching the right people.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `REMARKETY_GET_CAMPAIGNS` | Get Remarkety Campaigns | Tool to retrieve a list of marketing campaigns. Use when you need to page through campaigns with optional limit and skip. |
| `REMARKETY_GET_CUSTOMERS` | Get Remarkety Customers | Tool to retrieve customers. Use when you need to fetch a paginated list of customers from a Remarkety store. |
| `REMARKETY_REMARKETY_GET_PRODUCTS` | Get Remarkety Products | Tool to retrieve products. Use when you need to fetch a paginated list of products from a Remarkety store. |
| `REMARKETY_TRACK_CART` | Track Remarkety Cart | Tool to track cart events in Remarkety. Use after a customer updates their cart to sync cart data for remarketing. |
| `REMARKETY_UPLOAD_CONTACTS_BATCH` | Upload Contacts Batch | Tool to upload or update multiple contacts in batch. Use when you need to import or synchronize many contacts at once. |

## Supported Triggers

None listed.

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

The Remarkety MCP server is an implementation of the Model Context Protocol that connects your AI agent to Remarkety. It provides structured and secure access so your agent can perform Remarkety 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 Remarkety 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 Remarkety 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 Remarkety 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 Remarkety

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

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

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

## Related Toolkits

- [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.
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- [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.
- [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.
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- [Beamer](https://composio.dev/toolkits/beamer) - Beamer is a news and changelog platform for in-app announcements and feature updates. It helps companies boost user engagement by sharing news where users are most active.
- [Benchmark email](https://composio.dev/toolkits/benchmark_email) - Benchmark Email is a platform for creating, sending, and tracking email campaigns. It's built to help you engage audiences and analyze results—all in one place.
- [Bigmailer](https://composio.dev/toolkits/bigmailer) - BigMailer is an email marketing platform for managing multiple brands with white-labeling and automation. It helps teams streamline campaigns and simplify integration with Amazon SES.
- [Brandfetch](https://composio.dev/toolkits/brandfetch) - Brandfetch is an API that delivers company logos, colors, and visual branding assets. It helps marketers and developers keep brand visuals consistent everywhere.
- [Brevo](https://composio.dev/toolkits/brevo) - Brevo is an all-in-one email and SMS marketing platform for transactional messaging, automation, and CRM. It helps businesses engage customers and streamline communications through powerful campaign tools.
- [Campayn](https://composio.dev/toolkits/campayn) - Campayn is an email marketing platform for creating, sending, and managing campaigns. It helps businesses engage contacts and grow audiences with easy-to-use tools.
- [Cardly](https://composio.dev/toolkits/cardly) - Cardly is a platform for creating and sending personalized direct mail to customers. It helps businesses break through the digital clutter by getting real engagement via physical mailboxes.
- [ClickSend](https://composio.dev/toolkits/clicksend) - ClickSend is a cloud-based SMS and email marketing platform for businesses. It streamlines communication by enabling quick message delivery and contact management.
- [Crustdata](https://composio.dev/toolkits/crustdata) - CrustData is an AI-powered data intelligence platform for real-time company and people data. It helps B2B sales teams, AI SDRs, and investors react to live business signals.
- [Curated](https://composio.dev/toolkits/curated) - Curated is a platform for collecting, curating, and publishing newsletters. It streamlines content aggregation and distribution for creators and teams.
- [Customerio](https://composio.dev/toolkits/customerio) - Customer.io is a customer engagement platform for targeted messaging across email, SMS, and push. Easily automate, segment, and track communications with your audience.
- [Cutt ly](https://composio.dev/toolkits/cutt_ly) - Cutt.ly is a URL shortening service for managing and analyzing links. Streamline your workflows with quick, trackable, and branded short URLs.
- [Demio](https://composio.dev/toolkits/demio) - Demio is webinar software built for marketers, offering both live and automated sessions with interactive features. It helps teams engage audiences and optimize lead generation through detailed analytics.

## Frequently Asked Questions

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

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

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

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

---
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