# How to integrate Loops.so MCP with Autogen

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

## Introduction

This guide walks you through connecting Loops.so to AutoGen 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 AutoGen 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)
- [CrewAI](https://composio.dev/toolkits/loops_so/framework/crew-ai)

## TL;DR

Here's what you'll learn:
- Get and set up your OpenAI and Composio API keys
- Install the required dependencies for Autogen and Composio
- Initialize Composio and create a Tool Router session for Loops.so
- Wire that MCP URL into Autogen using McpWorkbench and StreamableHttpServerParams
- Configure an Autogen AssistantAgent that can call Loops.so tools
- Run a live chat loop where you ask the agent to perform Loops.so operations

## What is AutoGen?

Autogen is a framework for building multi-agent conversational AI systems from Microsoft. It enables you to create agents that can collaborate, use tools, and maintain complex workflows.
Key features include:
- Multi-Agent Systems: Build collaborative agent workflows
- MCP Workbench: Native support for Model Context Protocol tools
- Streaming HTTP: Connect to external services through streamable HTTP
- AssistantAgent: Pre-built agent class for tool-using assistants

## 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 agents and assistants directly to Loops.so. Instead of manually wiring Loops.so APIs, OAuth, and scopes yourself, you get a structured, tool-based interface that an LLM can call safely.
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

You will need:
- A Composio API key
- An OpenAI API key (used by Autogen's OpenAIChatCompletionClient)
- A Loops.so account you can connect to Composio
- Some basic familiarity with Autogen and Python async

### 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

Install Composio, Autogen extensions, and dotenv.
What's happening:
- composio connects your agent to Loops.so via MCP
- autogen-agentchat provides the AssistantAgent class
- autogen-ext-openai provides the OpenAI model client
- autogen-ext-tools provides MCP workbench support
```bash
pip install composio python-dotenv
pip install autogen-agentchat autogen-ext-openai autogen-ext-tools
```

### 3. Set up environment variables

Create a .env file in your project folder.
What's happening:
- COMPOSIO_API_KEY is required to talk to Composio
- OPENAI_API_KEY is used by Autogen's OpenAI client
- USER_ID is how Composio identifies which user's Loops.so connections to use
```bash
COMPOSIO_API_KEY=your-composio-api-key
OPENAI_API_KEY=your-openai-api-key
USER_ID=your-user-identifier@example.com
```

### 4. Import dependencies and create Tool Router session

What's happening:
- load_dotenv() reads your .env file
- Composio(api_key=...) initializes the SDK
- create(...) creates a Tool Router session that exposes Loops.so tools
- session.mcp.url is the MCP endpoint that Autogen will connect to
```python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio

from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient
from autogen_ext.tools.mcp import McpWorkbench, StreamableHttpServerParams

load_dotenv()

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

### 5. Configure MCP parameters for Autogen

Autogen expects parameters describing how to talk to the MCP server. That is what StreamableHttpServerParams is for.
What's happening:
- url points to the Tool Router MCP endpoint from Composio
- timeout is the HTTP timeout for requests
- sse_read_timeout controls how long to wait when streaming responses
- terminate_on_close=True cleans up the MCP server process when the workbench is closed
```python
# Configure MCP server parameters for Streamable HTTP
server_params = StreamableHttpServerParams(
    url=url,
    timeout=30.0,
    sse_read_timeout=300.0,
    terminate_on_close=True,
    headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")}
)
```

### 6. Create the model client and agent

What's happening:
- OpenAIChatCompletionClient wraps the OpenAI model for Autogen
- McpWorkbench connects the agent to the MCP tools
- AssistantAgent is configured with the Loops.so tools from the workbench
```python
# Create model client
model_client = OpenAIChatCompletionClient(
    model="gpt-5",
    api_key=os.getenv("OPENAI_API_KEY")
)

# Use McpWorkbench as context manager
async with McpWorkbench(server_params) as workbench:
    # Create Loops.so assistant agent with MCP tools
    agent = AssistantAgent(
        name="loops_so_assistant",
        description="An AI assistant that helps with Loops.so operations.",
        model_client=model_client,
        workbench=workbench,
        model_client_stream=True,
        max_tool_iterations=10
    )
```

### 7. Run the interactive chat loop

What's happening:
- The script prompts you in a loop with You:
- Autogen passes your input to the model, which decides which Loops.so tools to call via MCP
- agent.run_stream(...) yields streaming messages as the agent thinks and calls tools
- Typing exit, quit, or bye ends the loop
```python
print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
print("Ask any Loops.so related question or task to the agent.\n")

# Conversation loop
while True:
    user_input = input("You: ").strip()

    if user_input.lower() in ["exit", "quit", "bye"]:
        print("\nGoodbye!")
        break

    if not user_input:
        continue

    print("\nAgent is thinking...\n")

    # Run the agent with streaming
    try:
        response_text = ""
        async for message in agent.run_stream(task=user_input):
            if hasattr(message, "content") and message.content:
                response_text = message.content

        # Print the final response
        if response_text:
            print(f"Agent: {response_text}\n")
        else:
            print("Agent: I encountered an issue processing your request.\n")

    except Exception as e:
        print(f"Agent: Sorry, I encountered an error: {str(e)}\n")
```

## Complete Code

```python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio

from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient
from autogen_ext.tools.mcp import McpWorkbench, StreamableHttpServerParams

load_dotenv()

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

    # Configure MCP server parameters for Streamable HTTP
    server_params = StreamableHttpServerParams(
        url=url,
        timeout=30.0,
        sse_read_timeout=300.0,
        terminate_on_close=True,
        headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")}
    )

    # Create model client
    model_client = OpenAIChatCompletionClient(
        model="gpt-5",
        api_key=os.getenv("OPENAI_API_KEY")
    )

    # Use McpWorkbench as context manager
    async with McpWorkbench(server_params) as workbench:
        # Create Loops.so assistant agent with MCP tools
        agent = AssistantAgent(
            name="loops_so_assistant",
            description="An AI assistant that helps with Loops.so operations.",
            model_client=model_client,
            workbench=workbench,
            model_client_stream=True,
            max_tool_iterations=10
        )

        print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
        print("Ask any Loops.so related question or task to the agent.\n")

        # Conversation loop
        while True:
            user_input = input("You: ").strip()

            if user_input.lower() in ['exit', 'quit', 'bye']:
                print("\nGoodbye!")
                break

            if not user_input:
                continue

            print("\nAgent is thinking...\n")

            # Run the agent with streaming
            try:
                response_text = ""
                async for message in agent.run_stream(task=user_input):
                    if hasattr(message, 'content') and message.content:
                        response_text = message.content

                # Print the final response
                if response_text:
                    print(f"Agent: {response_text}\n")
                else:
                    print("Agent: I encountered an issue processing your request.\n")

            except Exception as e:
                print(f"Agent: Sorry, I encountered an error: {str(e)}\n")

if __name__ == "__main__":
    asyncio.run(main())
```

## Conclusion

You now have an Autogen assistant wired into Loops.so through Composio's Tool Router and MCP. From here you can:
- Add more toolkits to the toolkits list, for example notion or hubspot
- Refine the agent description to point it at specific workflows
- Wrap this script behind a UI, Slack bot, or internal tool
Once the pattern is clear for Loops.so, you can reuse the same structure for other MCP-enabled apps with minimal code changes.

## 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)
- [CrewAI](https://composio.dev/toolkits/loops_so/framework/crew-ai)

## Related Toolkits

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- [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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- [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.
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- [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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- [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 Autogen?

Yes, you can. Autogen 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)
