# How to integrate Loops.so MCP with CrewAI

```json
{
  "title": "How to integrate Loops.so MCP with CrewAI",
  "toolkit": "Loops.so",
  "toolkit_slug": "loops_so",
  "framework": "CrewAI",
  "framework_slug": "crew-ai",
  "url": "https://composio.dev/toolkits/loops_so/framework/crew-ai",
  "markdown_url": "https://composio.dev/toolkits/loops_so/framework/crew-ai.md",
  "updated_at": "2026-03-29T06:41:00.893Z"
}
```

## Introduction

This guide walks you through connecting Loops.so to CrewAI using the Composio tool router. By the end, you'll have a working Loops.so agent that can send onboarding email to new signups, segment contacts by plan and engagement, schedule a product update campaign through natural language commands.
This guide will help you understand how to give your CrewAI agent real control over a Loops.so account through Composio's Loops.so MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Loops.so with

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

## TL;DR

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

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

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `LOOPS_SO_CREATE_CONTACT` | Create Contact | Tool to add a new contact to your Loops audience. Use when you need to create a contact with email and optional properties like name, subscription status, or custom attributes. Returns 409 if contact already exists. |
| `LOOPS_SO_CREATE_CONTACT_PROPERTY` | Create Contact Property | Tool to add a custom contact property to your Loops team. Use when you need to store additional contact data beyond default fields. Properties must have unique names in camelCase format and a specified data type (string, number, boolean, or date). |
| `LOOPS_SO_DELETE_CONTACT` | Delete Contact | Tool to delete a contact by email address or user ID. Use when you need to remove a contact from Loops. Either email or userId must be provided to identify the contact. |
| `LOOPS_SO_FIND_CONTACT` | Find Contact | Tool to search for a contact by email or userId. Use when you need to find a specific contact's details including subscription status and custom properties. Exactly one of email or userId must be provided per request. |
| `LOOPS_SO_GET_CONTACT_PROPERTIES` | Get Contact Properties | Tool to retrieve a list of your account's contact properties from Loops.so. Use when you need to view all available contact properties or filter to only custom properties created by your team. |
| `LOOPS_SO_GET_DEDICATED_SENDING_IPS` | Get Dedicated Sending IPs | Tool to retrieve a list of Loops' dedicated sending IP addresses. Use when you need to get IP addresses for whitelisting purposes. |
| `LOOPS_SO_GET_MAILING_LISTS` | Get Mailing Lists | Tool to retrieve all mailing lists associated with your Loops account. Use when you need to browse or manage mailing list information. |
| `LOOPS_SO_LIST_CUSTOM_FIELDS` | List Custom Fields | Tool to retrieve a list of custom contact properties. Use when you need to view available custom fields for contacts. Note: This endpoint is deprecated in favor of 'List contact properties'. |
| `LOOPS_SO_LIST_TRANSACTIONAL_EMAILS` | List Transactional Emails | Tool to retrieve a list of published transactional emails. Use when you need to view all available transactional email templates. Supports pagination with perPage and cursor parameters. |
| `LOOPS_SO_SEND_EVENT` | Send Event | Tool to send events to trigger emails in Loops. Use when you need to track user actions and trigger automated email workflows based on those events. |
| `LOOPS_SO_TEST_API_KEY` | Test API Key | Tool to test API key validity and retrieve team information. Use to verify API credentials are working correctly. |
| `LOOPS_SO_UPDATE_CONTACT` | Update Contact | Tool to update an existing contact by email or userId. Use when you need to modify contact properties or re-subscribe contacts. Creates a new contact if no matching record exists. |

## Supported Triggers

None listed.

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

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

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

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

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

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

### Can I manage the permissions and scopes for Loops.so while using Tool Router?

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

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