How to integrate Printify MCP with CrewAI

This guide walks you through connecting Printify to CrewAI using the Composio tool router. By the end, you'll have a working Printify agent that can create draft products, review your orders, calculate shipping, list print providers, and manage webhooks through natural language commands. This guide will help you understand how to give your CrewAI agent real control over a Printify account through Composio's Printify MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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Printify is a print-on-demand platform for creating and selling custom products through connected merchant shops. It helps teams manage product catalogs, fulfillment, orders, uploads, and webhooks from one place.

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Introduction

This guide walks you through connecting Printify to CrewAI using the Composio tool router. By the end, you'll have a working Printify agent that can create draft products, review your orders, calculate shipping, list print providers, and manage webhooks through natural language commands.

This guide will help you understand how to give your CrewAI agent real control over a Printify account through Composio's Printify MCP server.

Before we dive in, let's take a quick look at the key ideas and tools involved.

Also integrate Printify with

OpenAI Agents SDKClaude Agent SDKClaude CodeClaude CoworkCodexOpenClawHermesCLIGoogle ADKLangChainVercel AI SDKMastra AILlamaIndex

TL;DR

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

The Printify MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Printify account. It provides structured and secure access to your shops, catalog, products, orders, images, and webhooks, so your agent can create products, manage listings, review orders, estimate shipping, and monitor shop events on your behalf.

  • Product creation and publishing: Have your agent create product drafts, update product details, publish selected changes to a connected sales channel, mark products as unpublished, or delete products.
  • Catalog and fulfillment research: Let the agent search product blueprints, review blueprint details, compare print providers and variants, and check available shipping methods and costs.
  • Order and shipping review: Direct your agent to list orders, retrieve complete order details, filter orders by fulfillment status or SKU, and calculate shipping estimates for proposed purchases.
  • Shop and image management: Instruct your agent to list your Printify shops, review products, upload artwork to your media library, list uploaded images, or archive images you no longer need.
  • Webhook management and testing: Have your agent create, review, update, delete, and test webhook subscriptions that notify your systems about Printify events.

What is the Composio tool router, and how does it fit here?

What is Composio SDK?

Composio's Composio SDK helps agents find the right tools for a task at runtime. You can plug in multiple toolkits (like Gmail, HubSpot, and GitHub), and the agent will identify the relevant app and action to complete multi-step workflows. This can reduce token usage and improve the reliability of tool calls. Read more here: Getting started with Composio SDK

The tool router generates a secure MCP URL that your agents can access to perform actions.

How the Composio SDK works

The Composio SDK follows a three-phase workflow:

  1. Discovery: Searches for tools matching your task and returns relevant toolkits with their details.
  2. Authentication: Checks for active connections. If missing, creates an auth config and returns a connection URL via Auth Link.
  3. Execution: Executes the action using the authenticated connection.

Step-by-step Guide

Step by step08 STEPS
1

Prerequisites

Before starting, make sure you have:
  • Python 3.9 or higher
  • A Composio account and API key
  • A Printify connection authorized in Composio
  • An OpenAI API key for the CrewAI LLM
  • Basic familiarity with Python
2

Getting API Keys for OpenAI and Composio

OpenAI API Key
  • Go to the OpenAI dashboard 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.
  • Navigate to your API settings and generate a new API key.
  • Store this key securely as you'll need it for authentication.
3

Install dependencies

bash
pip install composio crewai crewai-tools[mcp] python-dotenv
What's happening:
  • composio connects your agent to Printify via MCP
  • crewai provides Agent, Task, Crew, and LLM primitives
  • crewai-tools[mcp] includes MCP helpers
  • python-dotenv loads environment variables from .env
4

Set up environment variables

bash
COMPOSIO_API_KEY=your_composio_api_key_here
USER_ID=your_user_id_here
OPENAI_API_KEY=your_openai_api_key_here

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
5

Import dependencies

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")
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 Printify MCP URL
6

Create a Composio Tool Router session for Printify

python
composio_client = Composio(api_key=COMPOSIO_API_KEY)
session = composio_client.create(user_id=COMPOSIO_USER_ID, toolkits=["printify"])

url = session.mcp.url
What's happening:
  • You create a Printify only session through Composio
  • Composio returns an MCP HTTP URL that exposes Printify tools
7

Initialize the MCP Server

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,
    )
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.
8

Create a CLI Chatloop and define the Crew

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")
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.

Complete Code

Here's the complete code to get you started with Printify and CrewAI:

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=["printify"],
)
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 Printify through Composio's Tool Router. The agent can perform Printify 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
TOOLS

Supported Tools

Every Printify action and event your agent gets out of the box.

Archive Uploaded Image

Irreversibly archive an image in the connected merchant's Printify media library.

Calculate Order Shipping

Calculate available shipping-cost estimates for proposed line items and a destination.

Create Draft Product

Create a new product draft in a Printify shop.

Create Webhook

Create a persistent webhook subscription for a Printify shop.

Delete Product

Permanently delete a product from a Printify shop.

Delete Webhook

Permanently delete a Printify webhook subscription so future events are no longer delivered.

Get Blueprint

Get the full catalog record for one Printify product blueprint, including its description and images.

Get Order

Get complete details for one Printify order, including its recipient address, line items, status, shipping method, shipments, and timestamps.

Get Product

Get the complete Printify record for one product in a shop, including variants, print areas, images, visibility, and sales-channel properties.

Get Catalog Shipping Details

Get per-variant shipping costs and handling-time ranges for one advertised V2 shipping method.

List Blueprint Print Providers

List print providers that can fulfill a specific Printify blueprint.

List Blueprint Variants

List purchasable variants and print placeholders for a blueprint and print provider.

List Orders

Return one page of orders in a Printify shop, optionally filtered by provider status or exact SKU.

List Products

Return one page of products in a Printify shop.

List Catalog Shipping Methods

List the V2 shipping methods actually available for a Printify blueprint and print provider.

List Shops

List shops available to the connected Printify merchant account.

List Uploaded Images

Return one page of images in the connected merchant's Printify media library.

List Webhooks

List webhook subscriptions configured for a Printify shop.

Publish Product Changes

Start asynchronous publication of one or more fields selected in fields_to_publish from Printify to the shop's connected sales channel.

Search Catalog Blueprints

Search Printify's product blueprint catalog by case-insensitive text in title, brand, or model.

Simulate Webhook Event

Ask Printify to send a simulated event to an existing webhook's external callback URL.

Mark Product Unpublished

Notify Printify that a product has been unpublished from the connected sales channel.

Update Product Draft

Update selected fields of an existing Printify product.

Update Webhook URL

Replace the callback URL of an existing Printify webhook subscription.

Upload Image

Add an image to the connected merchant's Printify media library from either a public HTTP(S) URL or base64 content.

FRAMEWORKS

How to build Printify MCP Agent with another framework

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Printify MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Printify MCP with Claude Agent SDK

Claude Code logo

Claude Code

Use Printify MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Printify MCP with Claude Cowork

Codex logo

Codex

Use Printify MCP with Codex

OpenClaw logo

OpenClaw

Use Printify MCP with OpenClaw

Hermes logo

Hermes

Use Printify MCP with Hermes

CLI logo

CLI

Use Printify MCP with CLI

Google ADK logo

Google ADK

Use Printify MCP with Google ADK

LangChain logo

LangChain

Use Printify MCP with LangChain

Vercel AI SDK logo

Vercel AI SDK

Use Printify MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Printify MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Printify MCP with LlamaIndex

FAQ

Frequently asked questions

With a standalone Printify MCP server, the agents and LLMs can only access a fixed set of Printify tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Printify and many other apps based on the task at hand, all through a single MCP endpoint.

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 Printify tools.

Yes, absolutely. You can configure which Printify 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.

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 Printify data and credentials are handled as safely as possible.

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