# How to integrate Dpd2 MCP with LangChain

```json
{
  "title": "How to integrate Dpd2 MCP with LangChain",
  "toolkit": "Dpd2",
  "toolkit_slug": "dpd2",
  "framework": "LangChain",
  "framework_slug": "langchain",
  "url": "https://composio.dev/toolkits/dpd2/framework/langchain",
  "markdown_url": "https://composio.dev/toolkits/dpd2/framework/langchain.md",
  "updated_at": "2026-05-12T10:09:41.773Z"
}
```

## Introduction

This guide walks you through connecting Dpd2 to LangChain using the Composio tool router. By the end, you'll have a working Dpd2 agent that can list all storefronts in your dpd account, show recent purchases from last week, list all subscribers for a storefront through natural language commands.
This guide will help you understand how to give your LangChain agent real control over a Dpd2 account through Composio's Dpd2 MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Dpd2 with

- [OpenAI Agents SDK](https://composio.dev/toolkits/dpd2/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/dpd2/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/dpd2/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/dpd2/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/dpd2/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/dpd2/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/dpd2/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/dpd2/framework/cli)
- [Google ADK](https://composio.dev/toolkits/dpd2/framework/google-adk)
- [Vercel AI SDK](https://composio.dev/toolkits/dpd2/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/dpd2/framework/mastra-ai)
- [LlamaIndex](https://composio.dev/toolkits/dpd2/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/dpd2/framework/crew-ai)

## TL;DR

Here's what you'll learn:
- Get and set up your OpenAI and Composio API keys
- Connect your Dpd2 project to Composio
- Create a Tool Router MCP session for Dpd2
- Initialize an MCP client and retrieve Dpd2 tools
- Build a LangChain agent that can interact with Dpd2
- 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 Dpd2 MCP server, and what's possible with it?

The Dpd2 MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Dpd2 account. It provides structured and secure access to your storefronts, customers, purchases, and notifications, so your agent can perform actions like retrieving storefront details, listing customers, analyzing purchase data, and verifying notifications on your behalf.
- Storefront management and retrieval: Ask your agent to list all storefronts or fetch detailed metadata about a specific storefront by its ID for streamlined store operations.
- Customer listing and reporting: Effortlessly generate filtered or paginated lists of all Dpd2 customers, perfect for reporting, synchronization, or CRM workflows.
- Purchase data analysis: Have your agent pull detailed, filterable purchase records from your Dpd2 account for reporting, analytics, or bookkeeping tasks.
- Subscriber management: Quickly obtain lists of subscribers for any storefront, enabling targeted communication and subscriber insights.
- API health and notification verification: Ensure your Dpd2 API is online with connectivity checks or verify the authenticity of incoming webhook notifications for secure automation.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `DPD2_GET_STOREFRONT` | Get Storefront | Retrieves detailed information about a specific DPD storefront by its ID. Returns storefront configuration including name, URL, contact details, currency, type, and subdomain. Use this after obtaining a storefront ID from DPD2_LIST_STOREFRONTS or when you need to fetch current metadata for a known storefront. |
| `DPD2_LIST_CUSTOMERS2` | List DPD Customers (Filtered) | Tool to list customers in your DPD account with advanced filtering. Use when you need to find customers by email, name, product purchases, newsletter subscription status, or creation date range. |
| `DPD2_LIST_PURCHASES` | List DPD Purchases | Tool to list all purchases made through your DPD account. Use when you need to retrieve purchase records with optional date filters and pagination for reporting or analysis. |
| `DPD2_LIST_STOREFRONTS` | List Storefronts | Tool to list all storefronts in your DPD account. Use after authenticating to fetch storefront details before managing products or purchases. |
| `DPD2_LIST_SUBSCRIBERS` | List Subscribers | Tool to list subscribers for a given storefront. Use when you need a paginated and filtered list of subscribers after storefront setup. |
| `DPD2_PING` | DPD: Ping API | Tool to ping the API to check its status. Use when verifying API connectivity before further operations. |
| `DPD2_VERIFY_NOTIFICATION2` | Verify DPD IPN Notification | Tool to verify a POST from the URL integration (IPN/webhook). POST all parameters that were POSTed to your site to confirm authenticity. Use after receiving an IPN notification to validate it came from DPD. |
| `DPD2_VERIFY_SUBSCRIBER` | Verify Subscriber | Tool to verify a subscriber's subscription status. Use when you need to check if a subscriber is active and receiving service. Either username (email) or subscriber ID must be provided. |

## Supported Triggers

None listed.

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

The Dpd2 MCP server is an implementation of the Model Context Protocol that connects your AI agent to Dpd2. It provides structured and secure access so your agent can perform Dpd2 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 Dpd2 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 Dpd2 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 Dpd2 tools as needed
```python
# Create Tool Router session for Dpd2
session = composio.create(
    user_id=os.getenv("COMPOSIO_USER_ID"),
    toolkits=['dpd2']
)

url = session.mcp.url
```

```typescript
const session = await composio.create(
    userId as string,
    {
        toolkits: ['dpd2']
    }
);

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

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

No description provided.
```python
client = MultiServerMCPClient({
    "dpd2-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({
    "dpd2-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 Dpd2 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 Dpd2 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=['dpd2']
    )

    url = session.mcp.url
    
    client = MultiServerMCPClient({
        "dpd2-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 Dpd2 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: ['dpd2']
        }
    );

    const url = session.mcp.url;
    
    const client = new MultiServerMCPClient({
        "dpd2-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 Dpd2 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 Dpd2 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 Dpd2 MCP Agent with another framework

- [OpenAI Agents SDK](https://composio.dev/toolkits/dpd2/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/dpd2/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/dpd2/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/dpd2/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/dpd2/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/dpd2/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/dpd2/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/dpd2/framework/cli)
- [Google ADK](https://composio.dev/toolkits/dpd2/framework/google-adk)
- [Vercel AI SDK](https://composio.dev/toolkits/dpd2/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/dpd2/framework/mastra-ai)
- [LlamaIndex](https://composio.dev/toolkits/dpd2/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/dpd2/framework/crew-ai)

## Related Toolkits

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- [Baselinker](https://composio.dev/toolkits/baselinker) - BaseLinker is an all-in-one e-commerce management platform connecting stores, marketplaces, carriers, and more. It streamlines order processing, inventory control, and automates your sales operations.
- [Bestbuy](https://composio.dev/toolkits/bestbuy) - Best Buy is a leading retailer offering APIs for product, store, and recommendation data. Instantly access up-to-date retail insights for smarter shopping and decision-making.
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- [Cloudcart](https://composio.dev/toolkits/cloudcart) - CloudCart is an e-commerce platform for building and managing online stores. It helps businesses streamline product listings, orders, and customer engagement.
- [Countdown api](https://composio.dev/toolkits/countdown_api) - Countdown API gives you real-time, structured eBay product data, reviews, and seller feedback. Perfect for powering price monitoring, product research, or marketplace analytics workflows.
- [Finerworks](https://composio.dev/toolkits/finerworks) - FinerWorks is an online platform for fine art and photo printing services. Artists and photographers use it to order custom prints and manage print inventory efficiently.
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- [Fraudlabs pro](https://composio.dev/toolkits/fraudlabs_pro) - FraudLabs Pro is an online payment fraud detection service for e-commerce and merchants. It helps minimize chargebacks and revenue loss by detecting and preventing fraudulent transactions.
- [Gift up](https://composio.dev/toolkits/gift_up) - Gift Up! is a digital platform for selling, managing, and redeeming gift cards online. It streamlines promotions and gift card transactions for businesses and their customers.
- [Goody](https://composio.dev/toolkits/goody) - Goody is a gifting platform that lets users send gifts and physical products without handling logistics. It streamlines gifting by managing delivery, fulfillment, and recipient experience.
- [Gumroad](https://composio.dev/toolkits/gumroad) - Gumroad is a platform for selling digital products, physical goods, and memberships with a simple checkout and marketing tools. It streamlines creator payouts and helps you grow your audience effortlessly.
- [Instacart](https://composio.dev/toolkits/instacart) - Instacart is an online grocery delivery and pickup service platform. It lets you discover local retailers and create shoppable lists and recipes with ease.
- [Junglescout](https://composio.dev/toolkits/junglescout) - Junglescout is an Amazon product research and analytics platform for sellers. It delivers sales estimates, competitive insights, and optimization tools to boost your Amazon business.
- [Ko fi](https://composio.dev/toolkits/ko_fi) - Ko-fi is a platform that lets creators receive donations, memberships, and sales from fans. It helps creators monetize their work and grow their audience with minimal friction.
- [Lemon squeezy](https://composio.dev/toolkits/lemon_squeezy) - Lemon Squeezy is a payments and subscription platform built for software companies. It makes managing payments, taxes, and customer subscriptions effortless.
- [Loyverse](https://composio.dev/toolkits/loyverse) - Loyverse is a point-of-sale (POS) platform for small businesses, offering tools for sales, inventory, and customer loyalty. It helps streamline retail operations and boost customer engagement.
- [Memberstack](https://composio.dev/toolkits/memberstack) - Memberstack lets you add user authentication, payments, and member management to your website—no backend code required. Easily manage your site's members and subscriptions from a single platform.

## Frequently Asked Questions

### What are the differences in Tool Router MCP and Dpd2 MCP?

With a standalone Dpd2 MCP server, the agents and LLMs can only access a fixed set of Dpd2 tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Dpd2 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 Dpd2 tools.

### Can I manage the permissions and scopes for Dpd2 while using Tool Router?

Yes, absolutely. You can configure which Dpd2 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 Dpd2 data and credentials are handled as safely as possible.

---
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