# How to integrate Thanks io MCP with CrewAI

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

## Introduction

This guide walks you through connecting Thanks io to CrewAI 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 CrewAI 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)

## TL;DR

Here's what you'll learn:
- Get a Composio API key and configure your Thanks io connection
- Set up CrewAI with an MCP enabled agent
- Create a Tool Router session or standalone MCP server for Thanks io
- Build a conversational loop where your agent can execute Thanks io 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 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 agent to Thanks io. It provides structured and secure access so your agent can perform Thanks io 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 Thanks io 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 Thanks io 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 Thanks io 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 Thanks io

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

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=["thanks_io"],
)
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 Thanks io through Composio's Tool Router. The agent can perform Thanks io 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 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)

## 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.
- [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.
- [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.
- [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 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 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 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)