# How to integrate Sender MCP with LangChain

```json
{
  "title": "How to integrate Sender MCP with LangChain",
  "toolkit": "Sender",
  "toolkit_slug": "sender",
  "framework": "LangChain",
  "framework_slug": "langchain",
  "url": "https://composio.dev/toolkits/sender/framework/langchain",
  "markdown_url": "https://composio.dev/toolkits/sender/framework/langchain.md",
  "updated_at": "2026-03-29T06:49:27.339Z"
}
```

## Introduction

This guide walks you through connecting Sender to LangChain using the Composio tool router. By the end, you'll have a working Sender agent that can create a new email campaign for holiday sale, add a contact to your main subscriber list, get open rates for last week's campaigns through natural language commands.
This guide will help you understand how to give your LangChain agent real control over a Sender account through Composio's Sender MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Sender with

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

## TL;DR

Here's what you'll learn:
- Get and set up your OpenAI and Composio API keys
- Connect your Sender project to Composio
- Create a Tool Router MCP session for Sender
- Initialize an MCP client and retrieve Sender tools
- Build a LangChain agent that can interact with Sender
- 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 Sender MCP server, and what's possible with it?

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

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `SENDER_CREATE_FIELD` | Create Field | Tool to create a new custom subscriber field in Sender.net. Use when you need to add custom fields for email personalization, segmentation, or storing additional subscriber information like company name, birthday, job title, or other custom attributes. |
| `SENDER_CREATE_OR_UPDATE_SUBSCRIBER` | Create Or Update Subscriber | Tool to create a new subscriber or update an existing one in Sender.net. Use when you need to add new subscribers to your email list or update existing subscriber information. This performs an upsert operation - creates if the email doesn't exist, updates if it does. |
| `SENDER_GET_ALL_FIELDS` | Get All Fields | Tool to retrieve a list of all custom subscriber fields configured in the Sender.net account. Use when you need to view available fields for email personalization, segmentation, or managing subscriber data. |
| `SENDER_GET_ALL_WORKFLOWS` | Get All Workflows | Tool to retrieve a list of all automation workflows in the Sender account. Use when you need to view or manage automation workflows. |
| `SENDER_GET_CAMPAIGN_BY_ID` | Get Campaign By ID | Tool to retrieve a specific campaign by its unique ID from Sender. Use when you need detailed information about a campaign including delivery metrics and engagement statistics. |
| `SENDER_GET_GROUP_BY_ID` | Get Group By ID | Tool to retrieve a specific subscriber group by its unique ID from Sender. Use when you need detailed information about a single group including subscriber counts. |
| `SENDER_GET_SUBSCRIBER_BY_EMAIL` | Get Subscriber By Email | Tool to retrieve a specific subscriber by their email address from Sender. Use when you need to fetch detailed information about a single subscriber including their status, groups, and custom fields. |
| `SENDER_GET_SUBSCRIBER_BY_ID` | Get Subscriber By ID | Tool to retrieve a specific subscriber by their unique ID from Sender. Use when you need to fetch detailed information about a single subscriber including their status, groups, and custom fields. |
| `SENDER_UPDATE_SUBSCRIBER_FIELDS` | Update Subscriber Fields | Tool to update custom fields and information for an existing subscriber in Sender.net. Use when you need to modify subscriber details such as email, first name, last name, groups, or custom fields for email personalization and segmentation. |

## Supported Triggers

None listed.

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

The Sender MCP server is an implementation of the Model Context Protocol that connects your AI agent to Sender. It provides structured and secure access so your agent can perform Sender 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 Sender 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 Sender 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 Sender tools as needed
```python
# Create Tool Router session for Sender
session = composio.create(
    user_id=os.getenv("COMPOSIO_USER_ID"),
    toolkits=['sender']
)

url = session.mcp.url
```

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

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

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

No description provided.
```python
client = MultiServerMCPClient({
    "sender-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({
    "sender-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 Sender 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 Sender 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=['sender']
    )

    url = session.mcp.url
    
    client = MultiServerMCPClient({
        "sender-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 Sender 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: ['sender']
        }
    );

    const url = session.mcp.url;
    
    const client = new MultiServerMCPClient({
        "sender-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 Sender 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 Sender 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 Sender MCP Agent with another framework

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

## Related Toolkits

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- [Airtable](https://composio.dev/toolkits/airtable) - Airtable combines the flexibility of spreadsheets with the power of a database for easy project and data management. Teams use Airtable to organize, track, and collaborate with custom views and automations.
- [Asana](https://composio.dev/toolkits/asana) - Asana is a collaborative work management platform for teams to organize and track projects. It streamlines teamwork, boosts productivity, and keeps everyone aligned on goals.
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- [Linear](https://composio.dev/toolkits/linear) - Linear is a modern issue tracking and project planning tool for fast-moving teams. It helps streamline workflows, organize projects, and boost productivity.
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- [Monday](https://composio.dev/toolkits/monday) - Monday.com is a customizable work management platform for project planning and collaboration. It helps teams organize tasks, automate workflows, and track progress in real time.
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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.
- [Agiled](https://composio.dev/toolkits/agiled) - Agiled is an all-in-one business management platform for CRM, projects, and finance. It helps you streamline workflows, consolidate client data, and manage business processes in one place.
- [Ahrefs](https://composio.dev/toolkits/ahrefs) - Ahrefs is an SEO and marketing platform for site audits, keyword research, and competitor insights. It helps you improve search rankings and drive organic traffic.
- [Amcards](https://composio.dev/toolkits/amcards) - AMCards lets you create and mail personalized greeting cards online. Build stronger customer relationships with easy, automated card campaigns.
- [Ascora](https://composio.dev/toolkits/ascora) - Ascora is a cloud-based field service management platform for service businesses. It streamlines scheduling, invoicing, and customer operations in one place.
- [Basecamp](https://composio.dev/toolkits/basecamp) - Basecamp is a project management and team collaboration tool by 37signals. It helps teams organize tasks, share files, and communicate efficiently in one place.

## Frequently Asked Questions

### What are the differences in Tool Router MCP and Sender MCP?

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

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

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

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