# How to integrate Dpd2 MCP with CrewAI

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

## Introduction

This guide walks you through connecting Dpd2 to CrewAI 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 CrewAI 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)
- [LangChain](https://composio.dev/toolkits/dpd2/framework/langchain)
- [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)

## TL;DR

Here's what you'll learn:
- Get a Composio API key and configure your Dpd2 connection
- Set up CrewAI with an MCP enabled agent
- Create a Tool Router session or standalone MCP server for Dpd2
- Build a conversational loop where your agent can execute Dpd2 operations

## What is CrewAI?

CrewAI is a powerful framework for building multi-agent AI systems. It provides primitives for defining agents with specific roles, creating tasks, and orchestrating workflows through crews.
Key features include:
- Agent Roles: Define specialized agents with specific goals and backstories
- Task Management: Create tasks with clear descriptions and expected outputs
- Crew Orchestration: Combine agents and tasks into collaborative workflows
- MCP Integration: Connect to external tools through Model Context Protocol

## What is the 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

Before starting, make sure you have:
- Python 3.9 or higher
- A Composio account and API key
- A Dpd2 connection authorized in Composio
- An OpenAI API key for the CrewAI LLM
- Basic familiarity with Python

### 1. Getting API Keys for OpenAI and Composio

OpenAI API Key
- Go to the [OpenAI dashboard](https://platform.openai.com/settings/organization/api-keys) and create an API key. You'll need credits to use the models, or you can connect to another model provider.
- Keep the API key safe.
Composio API Key
- Log in to the [Composio dashboard](https://dashboard.composio.dev?utm_source=toolkits&utm_medium=framework_docs).
- Navigate to your API settings and generate a new API key.
- Store this key securely as you'll need it for authentication.

### 2. Install dependencies

**What's happening:**
- composio connects your agent to Dpd2 via MCP
- crewai provides Agent, Task, Crew, and LLM primitives
- crewai-tools[mcp] includes MCP helpers
- python-dotenv loads environment variables from .env
```bash
pip install composio crewai crewai-tools[mcp] python-dotenv
```

### 3. Set up environment variables

Create a .env file in your project root.
What's happening:
- COMPOSIO_API_KEY authenticates with Composio
- USER_ID scopes the session to your account
- OPENAI_API_KEY lets CrewAI use your chosen OpenAI model
```bash
COMPOSIO_API_KEY=your_composio_api_key_here
USER_ID=your_user_id_here
OPENAI_API_KEY=your_openai_api_key_here
```

### 4. Import dependencies

**What's happening:**
- CrewAI classes define agents and tasks, and run the workflow
- MCPServerHTTP connects the agent to an MCP endpoint
- Composio will give you a short lived Dpd2 MCP URL
```python
import os
from composio import Composio
from crewai import Agent, Task, Crew
from crewai_tools import MCPServerAdapter
import dotenv

dotenv.load_dotenv()

COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY")
COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID")

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

### 5. Create a Composio Tool Router session for Dpd2

**What's happening:**
- You create a Dpd2 only session through Composio
- Composio returns an MCP HTTP URL that exposes Dpd2 tools
```python
composio_client = Composio(api_key=COMPOSIO_API_KEY)
session = composio_client.create(user_id=COMPOSIO_USER_ID, toolkits=["dpd2"])

url = session.mcp.url
```

### 6. Initialize the MCP Server

**What's Happening:**
- Server Configuration: The code sets up connection parameters including the MCP server URL, streamable HTTP transport, and Composio API key authentication.
- MCP Adapter Bridge: MCPServerAdapter acts as a context manager that converts Composio MCP tools into a CrewAI-compatible format.
- Agent Setup: Creates a CrewAI Agent with a defined role (Search Assistant), goal (help with internet searches), and access to the MCP tools.
- Configuration Options: The agent includes settings like verbose=False for clean output and max_iter=10 to prevent infinite loops.
- Dynamic Tool Usage: Once created, the agent automatically accesses all Composio Search tools and decides when to use them based on user queries.
```python
server_params = {
    "url": url,
    "transport": "streamable-http",
    "headers": {"x-api-key": COMPOSIO_API_KEY},
}

with MCPServerAdapter(server_params) as tools:
    agent = Agent(
        role="Search Assistant",
        goal="Help users search the internet effectively",
        backstory="You are a helpful assistant with access to search tools.",
        tools=tools,
        verbose=False,
        max_iter=10,
    )
```

### 7. Create a CLI Chatloop and define the Crew

**What's Happening:**
- Interactive CLI Setup: The code creates an infinite loop that continuously prompts for user input and maintains the entire conversation history in a string variable.
- Input Validation: Empty inputs are ignored to prevent processing blank messages and keep the conversation clean.
- Context Building: Each user message is appended to the conversation context, which preserves the full dialogue history for better agent responses.
- Dynamic Task Creation: For every user input, a new Task is created that includes both the full conversation history and the current request as context.
- Crew Execution: A Crew is instantiated with the agent and task, then kicked off to process the request and generate a response.
- Response Management: The agent's response is converted to a string, added to the conversation context, and displayed to the user, maintaining conversational continuity.
```python
print("Chat started! Type 'exit' or 'quit' to end.\n")

conversation_context = ""

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

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

    if not user_input:
        continue

    conversation_context += f"\nUser: {user_input}\n"
    print("\nAgent is thinking...\n")

    task = Task(
        description=(
            f"Conversation history:\n{conversation_context}\n\n"
            f"Current request: {user_input}"
        ),
        expected_output="A helpful response addressing the user's request",
        agent=agent,
    )

    crew = Crew(agents=[agent], tasks=[task], verbose=False)
    result = crew.kickoff()
    response = str(result)

    conversation_context += f"Agent: {response}\n"
    print(f"Agent: {response}\n")
```

## Complete Code

```python
from crewai import Agent, Task, Crew, LLM
from crewai_tools import MCPServerAdapter
from composio import Composio
from dotenv import load_dotenv
import os

load_dotenv()

GOOGLE_API_KEY = os.getenv("GOOGLE_API_KEY")
COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY")
COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID")

if not GOOGLE_API_KEY:
    raise ValueError("GOOGLE_API_KEY is not set in the environment.")
if not COMPOSIO_API_KEY:
    raise ValueError("COMPOSIO_API_KEY is not set in the environment.")
if not COMPOSIO_USER_ID:
    raise ValueError("COMPOSIO_USER_ID is not set in the environment.")

# Initialize Composio and create a session
composio = Composio(api_key=COMPOSIO_API_KEY)
session = composio.create(
    user_id=COMPOSIO_USER_ID,
    toolkits=["dpd2"],
)
url = session.mcp.url

# Configure LLM
llm = LLM(
    model="gpt-5",
    api_key=os.getenv("OPENAI_API_KEY"),
)

server_params = {
    "url": url,
    "transport": "streamable-http",
    "headers": {"x-api-key": COMPOSIO_API_KEY},
}

with MCPServerAdapter(server_params) as tools:
    agent = Agent(
        role="Search Assistant",
        goal="Help users with internet searches",
        backstory="You are an expert assistant with access to Composio Search tools.",
        tools=tools,
        llm=llm,
        verbose=False,
        max_iter=10,
    )

    print("Chat started! Type 'exit' or 'quit' to end.\n")

    conversation_context = ""

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

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

        if not user_input:
            continue

        conversation_context += f"\nUser: {user_input}\n"
        print("\nAgent is thinking...\n")

        task = Task(
            description=(
                f"Conversation history:\n{conversation_context}\n\n"
                f"Current request: {user_input}"
            ),
            expected_output="A helpful response addressing the user's request",
            agent=agent,
        )

        crew = Crew(agents=[agent], tasks=[task], verbose=False)
        result = crew.kickoff()
        response = str(result)

        conversation_context += f"Agent: {response}\n"
        print(f"Agent: {response}\n")
```

## Conclusion

You now have a CrewAI agent connected to Dpd2 through Composio's Tool Router. The agent can perform Dpd2 operations through natural language commands.
Next steps:
- Add role-specific instructions to customize agent behavior
- Plug in more toolkits for multi-app workflows
- Chain tasks for complex multi-step operations

## How to build 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)
- [LangChain](https://composio.dev/toolkits/dpd2/framework/langchain)
- [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)

## Related Toolkits

- [Addresszen](https://composio.dev/toolkits/addresszen) - Addresszen is a real-time address autocomplete and verification service. It helps capture accurate, deliverable addresses with instant suggestions and validation.
- [Asin data api](https://composio.dev/toolkits/asin_data_api) - Asin data api gives you detailed, real-time product data from Amazon, including price, rank, and reviews. Perfect for e-commerce pros and data-driven marketers who need instant marketplace insights.
- [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.
- [Btcpay server](https://composio.dev/toolkits/btcpay_server) - BTCPay Server is a free, open-source, self-hosted Bitcoin payment processor. It lets merchants accept Bitcoin payments directly, cutting out middlemen and boosting privacy.
- [Cdr platform](https://composio.dev/toolkits/cdr_platform) - Cdr platform is an API for purchasing carbon dioxide removal services. It enables businesses to offset emissions by accessing verified carbon removal projects.
- [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.
- [Fingertip](https://composio.dev/toolkits/fingertip) - Fingertip is a business management platform for selling, booking, and customer engagement—all from a single link. It helps businesses streamline operations and connect with customers across social channels.
- [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 CrewAI?

Yes, you can. CrewAI fully supports MCP integration. You get structured tool calling, message history handling, and model orchestration while Tool Router takes care of discovering and serving the right 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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