# How to integrate Neverbounce MCP with LangChain

```json
{
  "title": "How to integrate Neverbounce MCP with LangChain",
  "toolkit": "Neverbounce",
  "toolkit_slug": "neverbounce",
  "framework": "LangChain",
  "framework_slug": "langchain",
  "url": "https://composio.dev/toolkits/neverbounce/framework/langchain",
  "markdown_url": "https://composio.dev/toolkits/neverbounce/framework/langchain.md",
  "updated_at": "2026-05-12T10:20:05.703Z"
}
```

## Introduction

This guide walks you through connecting Neverbounce to LangChain using the Composio tool router. By the end, you'll have a working Neverbounce agent that can verify a list of emails for bounces, download csv results from last bulk job, check your current neverbounce credit balance through natural language commands.
This guide will help you understand how to give your LangChain agent real control over a Neverbounce account through Composio's Neverbounce MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Neverbounce with

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

## TL;DR

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

The Neverbounce MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Neverbounce account. It provides structured and secure access to your email verification tools, so your agent can perform actions like bulk verifying lists, checking job statuses, downloading results, and managing your account seamlessly.
- Instant email verification and validation: Quickly verify email addresses for validity to reduce bounce rates and improve deliverability right from your agent.
- Bulk email job management: Create, start, and track bulk verification jobs for entire email lists, letting your agent handle large-scale email hygiene automatically.
- Automated job result retrieval: Download or fetch completed job results as CSVs or paginated data, making it easy to integrate verified emails into your workflows.
- Account usage and credit tracking: Let your agent monitor account stats, credits, and usage so you always know your verification capacity and performance.
- Secure job and data deletion: Direct your agent to permanently delete outdated or unnecessary jobs, ensuring your data remains clean and compliant.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `NEVERBOUNCE_ACCOUNT_INFO` | Get Account Info | Tool to get account information including credits, job counts, and usage statistics. Use when retrieving NeverBounce account summary after authentication. |
| `NEVERBOUNCE_CONFIRM_POE` | Confirm Proof of Email | Tool to confirm proof of email ownership (POE) from the JavaScript widget. Use when verifying server-side that a user confirmed their email through the widget. |
| `NEVERBOUNCE_JOBS_CREATE` | Create NeverBounce Bulk Verification Job | Tool to create a new bulk verification job with parsing, sampling, and callback options. Use for asynchronous list verification with advanced control. |
| `NEVERBOUNCE_JOBS_DELETE` | Delete NeverBounce Job | Tool to permanently delete a job and its results. Use when you need to irreversibly remove a bulk verification job. This delete is irreversible. |
| `NEVERBOUNCE_JOBS_DOWNLOAD_GET` | Download Job Results (GET) | Tool to download job results as a CSV file via GET. Use after job completion to retrieve segmented or enriched CSV output. |
| `NEVERBOUNCE_JOBS_RESULTS` | Retrieve Job Results | Tool to retrieve paginated results for a completed job, including original data and verification outcomes. Use after confirming job completion; avoid aggressive polling as repeated calls before completion risk rate limit errors. |
| `NEVERBOUNCE_JOBS_START` | Start NeverBounce Job | Tool to start a parsed job when auto_start is disabled. Use when you need to manually initiate a job that was created with auto_start=false. |
| `NEVERBOUNCE_JOBS_STATUS` | Get bulk job status | Tool to get the status and progress of a bulk verification job. Use when |
| `NEVERBOUNCE_PARSE_JOB` | Parse NeverBounce Job | Tool to parse a job created with auto_parse disabled. Use when you need to manually parse a job. Cannot reparse once parsed. |
| `NEVERBOUNCE_SEARCH_JOBS` | Search bulk verification jobs | Tool to search and list bulk verification jobs in your account with pagination and filtering. Use when retrieving jobs by id, filename, or status, or when listing all jobs with pagination. |
| `NEVERBOUNCE_SINGLE_CHECK` | NeverBounce Single Check | Tool to verify a single email address and gather additional information. Use when you need real-time validation at the point of entry. |
| `NEVERBOUNCE_WIDGET_SEND_EVENT` | JS Widget Send Event | Tool to send widget form events via the JS widget API. Use when reporting form.load or form.completion events after user interactions with your form. |

## Supported Triggers

None listed.

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

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

url = session.mcp.url
```

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

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

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

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

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

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

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

## Related Toolkits

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- [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.
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- [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 Neverbounce MCP?

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

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

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

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