# How to integrate Thanks io MCP with Autogen

```json
{
  "title": "How to integrate Thanks io MCP with Autogen",
  "toolkit": "Thanks io",
  "toolkit_slug": "thanks_io",
  "framework": "AutoGen",
  "framework_slug": "autogen",
  "url": "https://composio.dev/toolkits/thanks_io/framework/autogen",
  "markdown_url": "https://composio.dev/toolkits/thanks_io/framework/autogen.md",
  "updated_at": "2026-05-12T10:28:21.213Z"
}
```

## Introduction

This guide walks you through connecting Thanks io to AutoGen using the Composio tool router. By the end, you'll have a working Thanks io agent that can add new customer to holiday mailing list, show all available handwritten font styles, create a mailing list for event attendees through natural language commands.
This guide will help you understand how to give your AutoGen agent real control over a Thanks io account through Composio's Thanks io MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Thanks io with

- [OpenAI Agents SDK](https://composio.dev/toolkits/thanks_io/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/thanks_io/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/thanks_io/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/thanks_io/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/thanks_io/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/thanks_io/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/thanks_io/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/thanks_io/framework/cli)
- [Google ADK](https://composio.dev/toolkits/thanks_io/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/thanks_io/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/thanks_io/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/thanks_io/framework/mastra-ai)
- [LlamaIndex](https://composio.dev/toolkits/thanks_io/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/thanks_io/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 Thanks io
- Wire that MCP URL into Autogen using McpWorkbench and StreamableHttpServerParams
- Configure an Autogen AssistantAgent that can call Thanks io tools
- Run a live chat loop where you ask the agent to perform Thanks io 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 Thanks io MCP server, and what's possible with it?

The Thanks io MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Thanks io account. It provides structured and secure access to your direct mail platform, so your agent can perform actions like managing mailing lists, sending personalized postcards, choosing templates, and handling recipients automatically on your behalf.
- Mailing list management: Effortlessly create, list, or delete mailing lists, and keep your recipient groups organized for targeted campaigns.
- Recipient automation: Quickly add or remove recipients from mailing lists, ensuring your contacts are always up to date and ready for new mailings.
- Personalized mail creation: Enable your agent to select from available handwriting styles or image templates, so every postcard, letter, or notecard feels truly unique.
- Template selection and preview: Browse and choose from message and image templates to customize your direct mail content for any occasion.
- Automated sending workflows: Trigger stored send actions to deliver mailings at the right moment, keeping your outreach timely and efficient.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `THANKS_IO_ADD_RECIPIENT_TO_MAILING_LIST` | Add Recipient to Mailing List | Tool to add a new recipient to a mailing list. Use after confirming recipient and list IDs. |
| `THANKS_IO_CREATE_MAILING_LIST` | Create Mailing List | Tool to create a new mailing list. Use when you need to group contacts under a fresh list before adding recipients. |
| `THANKS_IO_DELETE_MAILING_LIST` | Delete Mailing List | Tool to delete a mailing list. Use when you need to remove an entire mailing list by its ID. Confirm the list ID before calling. Example: "Delete the mailing list with ID 123e4567-e89b-12d3-a456-426614174000". |
| `THANKS_IO_DELETE_RECIPIENT_FROM_MAILING_LIST` | Delete Recipient from Mailing List | Tool to remove a recipient from a mailing list. Use after confirming the recipient's ID. |
| `THANKS_IO_DELETE_SUB_ACCOUNT` | Delete Sub-Account | Tool to delete a specific sub-account by ID. Use when you need to remove an existing sub-account. Confirm the ID before calling. |
| `THANKS_IO_EXECUTE_STORED_SEND` | Execute Stored Send | Tool to execute a previously created stored send. Use after creating a stored send to trigger delivery. The response body is empty; success is indicated by a 200 or 204 status. |
| `THANKS_IO_LIST_HANDWRITING_STYLES` | List Handwriting Styles | Tool to retrieve available handwriting styles. Use when selecting a style for handwritten personalization. |
| `THANKS_IO_LIST_IMAGE_TEMPLATES` | List Image Templates | Tool to retrieve a list of available image templates. Use when you need to browse or select a template for mailings. |
| `THANKS_IO_LIST_MAILING_LISTS` | List Mailing Lists | Tool to list all mailing lists. Use when you need to fetch existing lists before managing recipients. |
| `THANKS_IO_LIST_MESSAGE_TEMPLATES` | List Message Templates | Tool to list available message templates. Use when selecting a template for a mailing. |
| `THANKS_IO_MAILING_LISTS_BUY_RADIUS_SEARCH` | Buy Radius Search Mailing List | Tool to buy or append a radius search mailing list based on address and radius. Use when you need targeted mailing lists around a specified address. |
| `THANKS_IO_ORDER_PREVIEW_LETTER` | Preview letter send | Tool to preview a letter send as PDF. Use when you need to confirm letter content before placing the final order. Returns PDF preview URLs. |
| `THANKS_IO_ORDER_PREVIEW_NOTECARD` | Preview Notecard | Tool to preview a notecard send. Use when you need front and back images before placing an actual notecard order. |
| `THANKS_IO_ORDER_PREVIEW_WINDOWLESS_LETTER` | Preview Windowless Letter | Tool to preview a windowless letter send. Use when you need a PDF preview of the cover-only letter before placing an order. |
| `THANKS_IO_ORDERS_LIST` | List Orders | Tool to list recent orders. Use after placing orders to fetch the latest history, optionally filtering by sub-account or limiting the result count. |
| `THANKS_IO_ORDERS_SEARCH_BY_ADDRESS` | Search Orders by Recipient Street Address | Tool to search orders by recipient street address. Use when you need to find all orders sent to a specific street address. |
| `THANKS_IO_RECIPIENTS_CREATE_MULTI` | Create Multiple Recipients | Tool to create multiple recipients at once in a mailing list. Use when batching recipient additions for efficiency. |
| `THANKS_IO_RECIPIENTS_DELETE_BY_ADDRESS` | Delete Recipient by Address | Tool to delete a recipient by address and postal code. Use when you need to remove a recipient without their ID. |
| `THANKS_IO_RECIPIENTS_GET_DETAILS` | Get Recipient Details | Tool to get details for a specific recipient by ID. Use to verify a recipient’s full address and custom fields. |
| `THANKS_IO_RECIPIENTS_SEARCH_BY_EMAIL` | Search Recipients by Email | Tool to search recipients by email across mailing lists. Use when you need to find all recipients matching an email in specific lists. Example: "Find recipients with email test@test.com in lists [1,2,3]." |
| `THANKS_IO_RECIPIENTS_UPDATE` | Update Recipient | Tool to update existing recipient details by recipient ID. Use when modifying recipient data after confirming the recipient exists. |
| `THANKS_IO_SEND_POSTCARD` | Send Postcard | Tool to send a customized postcard. Use when you need to dispatch a physical postcard with a chosen image and handwritten message. |
| `THANKS_IO_STORED_SEND_NOTECARD` | Stored Send Notecard | Tool to create a stored send for a notecard. Use when you need to schedule mailing of a personalized notecard at a later time after preparing payload. |
| `THANKS_IO_STORED_SEND_POSTCARD` | Stored Send Postcard | Tool to create a stored send for a postcard. Use when you need to prepare and schedule postcard orders for later execution; returns a URL to finalize and send. |
| `THANKS_IO_STORED_SEND_WINDOWLESS_LETTER` | Stored Send Windowless Letter | Tool to create a stored send for a windowless letter. Use when you need to prepare a letter order for later execution. |
| `THANKS_IO_SUB_ACCOUNTS_CREATE` | Create Sub-Account | Tool to create a new sub-account. Use when you need to manage separate profiles with distinct return addresses and settings. |
| `THANKS_IO_SUB_ACCOUNTS_LIST` | List Sub Accounts | Tool to list all available sub-accounts. Use when you need to select a sub-account for operations requiring a sub-account context. |
| `THANKS_IO_SUB_ACCOUNTS_SHOW` | Get Sub Account Details | Tool to retrieve details for a specific sub-account by ID. Use when you need full configuration of a sub-account before performing sub-account scoped operations. |
| `THANKS_IO_SUB_ACCOUNTS_UPDATE` | Update Sub-Account | Tool to update details for a specific sub-account. Use when modifying title or return address details of a sub-account. Confirm sub-account ID before calling. |

## Supported Triggers

None listed.

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

The Thanks io MCP server is an implementation of the Model Context Protocol that connects your AI agents and assistants directly to Thanks io. Instead of manually wiring Thanks io 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 Thanks io 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 Thanks io 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 Thanks io 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 Thanks io 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 Thanks io session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["thanks_io"]
    )
    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 Thanks io 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 Thanks io assistant agent with MCP tools
    agent = AssistantAgent(
        name="thanks_io_assistant",
        description="An AI assistant that helps with Thanks io 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 Thanks io 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 Thanks io 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 Thanks io session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["thanks_io"]
    )
    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 Thanks io assistant agent with MCP tools
        agent = AssistantAgent(
            name="thanks_io_assistant",
            description="An AI assistant that helps with Thanks io 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 Thanks io 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 Thanks io 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 Thanks io, you can reuse the same structure for other MCP-enabled apps with minimal code changes.

## How to build Thanks io MCP Agent with another framework

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

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- [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.
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- [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 Thanks io MCP?

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

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

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

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