# How to integrate Thanks io MCP with LangChain

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

## Introduction

This guide walks you through connecting Thanks io to LangChain 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 LangChain 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)
- [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
- Connect your Thanks io project to Composio
- Create a Tool Router MCP session for Thanks io
- Initialize an MCP client and retrieve Thanks io tools
- Build a LangChain agent that can interact with Thanks io
- Set up an interactive chat interface for testing

## What is LangChain?

LangChain is a framework for developing applications powered by language models. It provides tools and abstractions for building agents that can reason, use tools, and maintain conversation context.
Key features include:
- Agent Framework: Build agents that can use tools and make decisions
- MCP Integration: Connect to external services through Model Context Protocol adapters
- Memory Management: Maintain conversation history across interactions
- Multi-Provider Support: Works with OpenAI, Anthropic, and other LLM providers

## 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

No description provided.

### 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

No description provided.
```python
pip install composio-langchain langchain-mcp-adapters langchain python-dotenv
```

```typescript
npm install @composio/langchain @langchain/core @langchain/openai @langchain/mcp-adapters dotenv
```

### 3. Set up environment variables

Create a .env file in your project root.
What's happening:
- COMPOSIO_API_KEY authenticates your requests to Composio's API
- COMPOSIO_USER_ID identifies the user for session management
- OPENAI_API_KEY enables access to OpenAI's language models
```bash
COMPOSIO_API_KEY=your_composio_api_key_here
COMPOSIO_USER_ID=your_composio_user_id_here
OPENAI_API_KEY=your_openai_api_key_here
```

### 4. Import dependencies

No description provided.
```python
from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain.agents import create_agent
from dotenv import load_dotenv
from composio import Composio
import asyncio
import os

load_dotenv()
```

```typescript
import { Composio } from '@composio/core';
import { LangchainProvider } from '@composio/langchain';
import { MultiServerMCPClient } from "@langchain/mcp-adapters";
import { createAgent } from "langchain";
import * as readline from 'readline';
import 'dotenv/config';

dotenv.config();
```

### 5. Initialize Composio client

What's happening:
- We're loading the COMPOSIO_API_KEY from environment variables and validating it exists
- Creating a Composio instance that will manage our connection to Thanks io tools
- Validating that COMPOSIO_USER_ID is also set before proceeding
```python
async def main():
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))

    if not os.getenv("COMPOSIO_API_KEY"):
        raise ValueError("COMPOSIO_API_KEY is not set")
    if not os.getenv("COMPOSIO_USER_ID"):
        raise ValueError("COMPOSIO_USER_ID is not set")
```

```typescript
const composioApiKey = process.env.COMPOSIO_API_KEY;
const userId = process.env.COMPOSIO_USER_ID;

if (!composioApiKey) throw new Error('COMPOSIO_API_KEY is not set');
if (!userId) throw new Error('COMPOSIO_USER_ID is not set');

async function main() {
    const composio = new Composio({
        apiKey: composioApiKey as string,
        provider: new LangchainProvider()
    });
```

### 6. Create a Tool Router session

What's happening:
- We're creating a Tool Router session that gives your agent access to Thanks io tools
- The create method takes the user ID and specifies which toolkits should be available
- The returned session.mcp.url is the MCP server URL that your agent will use
- This approach allows the agent to dynamically load and use Thanks io tools as needed
```python
# Create Tool Router session for Thanks io
session = composio.create(
    user_id=os.getenv("COMPOSIO_USER_ID"),
    toolkits=['thanks_io']
)

url = session.mcp.url
```

```typescript
const session = await composio.create(
    userId as string,
    {
        toolkits: ['thanks_io']
    }
);

const url = session.mcp.url;
```

### 7. Configure the agent with the MCP URL

No description provided.
```python
client = MultiServerMCPClient({
    "thanks_io-agent": {
        "transport": "streamable_http",
        "url": session.mcp.url,
        "headers": {
            "x-api-key": os.getenv("COMPOSIO_API_KEY")
        }
    }
})

tools = await client.get_tools()

agent = create_agent("gpt-5", tools)
```

```typescript
const client = new MultiServerMCPClient({
    "thanks_io-agent": {
        transport: "http",
        url: url,
        headers: {
            "x-api-key": process.env.COMPOSIO_API_KEY
        }
    }
});

const tools = await client.getTools();

const agent = createAgent({ model: "gpt-5", tools });
```

### 8. Set up interactive chat interface

No description provided.
```python
conversation_history = []

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")

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

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

    if not user_input:
        continue

    conversation_history.append({"role": "user", "content": user_input})
    print("\nAgent is thinking...\n")

    response = await agent.ainvoke({"messages": conversation_history})
    conversation_history = response['messages']
    final_response = response['messages'][-1].content
    print(f"Agent: {final_response}\n")
```

```typescript
let conversationHistory: any[] = [];

console.log("Chat started! Type 'exit' or 'quit' to end the conversation.\n");
console.log("Ask any Thanks io related question or task to the agent.\n");

const rl = readline.createInterface({
    input: process.stdin,
    output: process.stdout,
    prompt: 'You: '
});

rl.prompt();

rl.on('line', async (userInput: string) => {
    const trimmedInput = userInput.trim();

    if (['exit', 'quit', 'bye'].includes(trimmedInput.toLowerCase())) {
        console.log("\nGoodbye!");
        rl.close();
        process.exit(0);
    }

    if (!trimmedInput) {
        rl.prompt();
        return;
    }

    conversationHistory.push({ role: "user", content: trimmedInput });
    console.log("\nAgent is thinking...\n");

    const response = await agent.invoke({ messages: conversationHistory });
    conversationHistory = response.messages;

    const finalResponse = response.messages[response.messages.length - 1]?.content;
    console.log(`Agent: ${finalResponse}\n`);
        
        rl.prompt();
    });

    rl.on('close', () => {
        console.log('\n👋 Session ended.');
        process.exit(0);
    });
```

### 9. Run the application

No description provided.
```python
if __name__ == "__main__":
    asyncio.run(main())
```

```typescript
main().catch((err) => {
    console.error('Fatal error:', err);
    process.exit(1);
});
```

## Complete Code

```python
from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain.agents import create_agent
from dotenv import load_dotenv
from composio import Composio
import asyncio
import os

load_dotenv()

async def main():
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    
    if not os.getenv("COMPOSIO_API_KEY"):
        raise ValueError("COMPOSIO_API_KEY is not set")
    if not os.getenv("COMPOSIO_USER_ID"):
        raise ValueError("COMPOSIO_USER_ID is not set")
    
    session = composio.create(
        user_id=os.getenv("COMPOSIO_USER_ID"),
        toolkits=['thanks_io']
    )

    url = session.mcp.url
    
    client = MultiServerMCPClient({
        "thanks_io-agent": {
            "transport": "streamable_http",
            "url": url,
            "headers": {
                "x-api-key": os.getenv("COMPOSIO_API_KEY")
            }
        }
    })
    
    tools = await client.get_tools()
  
    agent = create_agent("gpt-5", tools)
    
    conversation_history = []
    
    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")
    
    while True:
        user_input = input("You: ").strip()
        
        if user_input.lower() in ['exit', 'quit', 'bye']:
            print("\nGoodbye!")
            break
        
        if not user_input:
            continue
        
        conversation_history.append({"role": "user", "content": user_input})
        print("\nAgent is thinking...\n")
        
        response = await agent.ainvoke({"messages": conversation_history})
        conversation_history = response['messages']
        final_response = response['messages'][-1].content
        print(f"Agent: {final_response}\n")

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

```typescript
import { Composio } from '@composio/core';
import { LangchainProvider } from '@composio/langchain';
import { MultiServerMCPClient } from "@langchain/mcp-adapters";  
import { createAgent } from "langchain";
import * as readline from 'readline';
import 'dotenv/config';

const composioApiKey = process.env.COMPOSIO_API_KEY;
const userId = process.env.COMPOSIO_USER_ID;

if (!composioApiKey) throw new Error('COMPOSIO_API_KEY is not set');
if (!userId) throw new Error('COMPOSIO_USER_ID is not set');

async function main() {
    const composio = new Composio({
        apiKey: composioApiKey as string,
        provider: new LangchainProvider()
    });

    const session = await composio.create(
        userId as string,
        {
            toolkits: ['thanks_io']
        }
    );

    const url = session.mcp.url;
    
    const client = new MultiServerMCPClient({
        "thanks_io-agent": {
            transport: "http",
            url: url,
            headers: {
                "x-api-key": process.env.COMPOSIO_API_KEY
            }
        }
    });
    
    const tools = await client.getTools();
  
    const agent = createAgent({ model: "gpt-5", tools });
    
    let conversationHistory: any[] = [];
    
    console.log("Chat started! Type 'exit' or 'quit' to end the conversation.\n");
    console.log("Ask any Thanks io related question or task to the agent.\n");
    
    const rl = readline.createInterface({
        input: process.stdin,
        output: process.stdout,
        prompt: 'You: '
    });

    rl.prompt();

    rl.on('line', async (userInput: string) => {
        const trimmedInput = userInput.trim();
        
        if (['exit', 'quit', 'bye'].includes(trimmedInput.toLowerCase())) {
            console.log("\nGoodbye!");
            rl.close();
            process.exit(0);
        }
        
        if (!trimmedInput) {
            rl.prompt();
            return;
        }
        
        conversationHistory.push({ role: "user", content: trimmedInput });
        console.log("\nAgent is thinking...\n");
        
        const response = await agent.invoke({ messages: conversationHistory });
        conversationHistory = response.messages;
        
        const finalResponse = response.messages[response.messages.length - 1]?.content;
        console.log(`Agent: ${finalResponse}\n`);
        
        rl.prompt();
    });

    rl.on('close', () => {
        console.log('\nSession ended.');
        process.exit(0);
    });
}

main().catch((err) => {
    console.error('Fatal error:', err);
    process.exit(1);
});
```

## Conclusion

You've successfully built a LangChain agent that can interact with Thanks io through Composio's Tool Router.
Key features of this implementation:
- Dynamic tool loading through Composio's Tool Router
- Conversation history maintenance for context-aware responses
- Async Python provides clean, efficient execution of agent workflows
You can extend this further by adding error handling, implementing specific business logic, or integrating additional Composio toolkits to create multi-app workflows.

## 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)
- [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)

## 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 LangChain?

Yes, you can. LangChain 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)