# How to integrate Retailed MCP with CrewAI ```json { "title": "How to integrate Retailed MCP with CrewAI", "toolkit": "Retailed", "toolkit_slug": "retailed", "framework": "CrewAI", "framework_slug": "crew-ai", "url": "https://composio.dev/toolkits/retailed/framework/crew-ai", "markdown_url": "https://composio.dev/toolkits/retailed/framework/crew-ai.md", "updated_at": "2026-05-12T10:24:02.734Z" } ``` ## Introduction This guide walks you through connecting Retailed to CrewAI using the Composio tool router. By the end, you'll have a working Retailed agent that can show current goat prices for product id 12345, find trending sneakers on stockx today, get stockx details for sku aq2667-200 through natural language commands. This guide will help you understand how to give your CrewAI agent real control over a Retailed account through Composio's Retailed MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved. ## Also integrate Retailed with - [OpenAI Agents SDK](https://composio.dev/toolkits/retailed/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/retailed/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/retailed/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/retailed/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/retailed/framework/codex) - [OpenClaw](https://composio.dev/toolkits/retailed/framework/openclaw) - [Hermes](https://composio.dev/toolkits/retailed/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/retailed/framework/cli) - [Google ADK](https://composio.dev/toolkits/retailed/framework/google-adk) - [LangChain](https://composio.dev/toolkits/retailed/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/retailed/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/retailed/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/retailed/framework/llama-index) ## TL;DR Here's what you'll learn: - Get a Composio API key and configure your Retailed connection - Set up CrewAI with an MCP enabled agent - Create a Tool Router session or standalone MCP server for Retailed - Build a conversational loop where your agent can execute Retailed 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 Retailed MCP server, and what's possible with it? The Retailed MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Retailed account. It provides structured and secure access to your retail data and e-commerce integrations, so your agent can perform actions like product searches, dynamic price retrieval, trend analysis, inventory checks, and API usage monitoring on your behalf. - Real-time product search and discovery: Instantly search for products across supported platforms and retrieve detailed information based on your custom criteria. - Dynamic pricing and size-based quotes: Ask your agent to pull the latest pricing for specific products and sizes from marketplaces like GOAT and StockX. - Trend analysis and market insights: Have the agent surface the latest trending products from StockX, helping you spot opportunities and popular items quickly. - Comprehensive product metadata access: Retrieve in-depth product metadata from StockX by SKU or URL for more informed decisions and listings. - API usage and quota monitoring: Let your agent track your current API usage statistics, so you stay on top of your account limits and avoid surprises. ## Supported Tools | Tool slug | Name | Description | |---|---|---| | `RETAILED_GET_GOAT_PRICES` | Get GOAT Product Prices | Tool to retrieve pricing information for a specific product on GOAT. Use when you need up-to-date size-based pricing. Call after confirming product_id. | | `RETAILED_GET_STOCK_X_PRODUCT` | Get StockX Product | Tool to retrieve detailed StockX product information, including variant-level data. Use when you need comprehensive metadata from StockX by SKU or URL. Response is structured per variant; aggregate price or inventory metrics across variants only after grouping by variant to avoid distortion. | | `RETAILED_GET_STOCKX_SEARCH` | StockX Search | Tool to search StockX marketplace for products and pricing information. Use when you have a search term and need up-to-date listings on StockX. Note: SKU identifiers and size labels in results may differ from other marketplaces (e.g., GOAT); normalize these fields before cross-platform price comparisons. | | `RETAILED_GET_STOCKX_TRENDS` | StockX Trends | Tool to get the latest trending products from StockX. Use when you want to discover current trending items. | | `RETAILED_GET_USAGE` | Get API Usage | Tool to retrieve current API usage statistics. The only mechanism to check remaining API credits; call proactively before long-running analyses to prevent mid-run quota exhaustion. | | `RETAILED_SEARCH_PRODUCTS` | Search Products | Search for products in Retailed database matching query criteria. Uses Retailed's granular querying language with support for filtering by name, SKU, brand. SKUs and size labels are not standardized across sources; normalize product IDs and size labels before comparing results across marketplaces. | ## Supported Triggers None listed. ## Creating MCP Server - Stand-alone vs Composio SDK The Retailed MCP server is an implementation of the Model Context Protocol that connects your AI agent to Retailed. It provides structured and secure access so your agent can perform Retailed 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 Retailed 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 Retailed 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 Retailed 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 Retailed **What's happening:** - You create a Retailed only session through Composio - Composio returns an MCP HTTP URL that exposes Retailed tools ```python composio_client = Composio(api_key=COMPOSIO_API_KEY) session = composio_client.create(user_id=COMPOSIO_USER_ID, toolkits=["retailed"]) 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=["retailed"], ) 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 Retailed through Composio's Tool Router. The agent can perform Retailed 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 Retailed MCP Agent with another framework - [OpenAI Agents SDK](https://composio.dev/toolkits/retailed/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/retailed/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/retailed/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/retailed/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/retailed/framework/codex) - [OpenClaw](https://composio.dev/toolkits/retailed/framework/openclaw) - [Hermes](https://composio.dev/toolkits/retailed/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/retailed/framework/cli) - [Google ADK](https://composio.dev/toolkits/retailed/framework/google-adk) - [LangChain](https://composio.dev/toolkits/retailed/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/retailed/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/retailed/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/retailed/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. - [Dpd2](https://composio.dev/toolkits/dpd2) - Dpd2 is a robust email management platform for handling, sorting, and automating email workflows. Streamline your communications and boost productivity with advanced sorting, labeling, and response tools. - [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. ## Frequently Asked Questions ### What are the differences in Tool Router MCP and Retailed MCP? With a standalone Retailed MCP server, the agents and LLMs can only access a fixed set of Retailed tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Retailed 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 Retailed tools. ### Can I manage the permissions and scopes for Retailed while using Tool Router? Yes, absolutely. You can configure which Retailed 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 Retailed data and credentials are handled as safely as possible. --- [See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)