# How to integrate Retailed MCP with Autogen ```json { "title": "How to integrate Retailed MCP with Autogen", "toolkit": "Retailed", "toolkit_slug": "retailed", "framework": "AutoGen", "framework_slug": "autogen", "url": "https://composio.dev/toolkits/retailed/framework/autogen", "markdown_url": "https://composio.dev/toolkits/retailed/framework/autogen.md", "updated_at": "2026-05-12T10:24:02.734Z" } ``` ## Introduction This guide walks you through connecting Retailed to AutoGen 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 AutoGen 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) - [CrewAI](https://composio.dev/toolkits/retailed/framework/crew-ai) ## TL;DR Here's what you'll learn: - Get and set up your OpenAI and Composio API keys - Install the required dependencies for Autogen and Composio - Initialize Composio and create a Tool Router session for Retailed - Wire that MCP URL into Autogen using McpWorkbench and StreamableHttpServerParams - Configure an Autogen AssistantAgent that can call Retailed tools - Run a live chat loop where you ask the agent to perform Retailed operations ## What is AutoGen? Autogen is a framework for building multi-agent conversational AI systems from Microsoft. It enables you to create agents that can collaborate, use tools, and maintain complex workflows. Key features include: - Multi-Agent Systems: Build collaborative agent workflows - MCP Workbench: Native support for Model Context Protocol tools - Streaming HTTP: Connect to external services through streamable HTTP - AssistantAgent: Pre-built agent class for tool-using assistants ## 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 agents and assistants directly to Retailed. Instead of manually wiring Retailed APIs, OAuth, and scopes yourself, you get a structured, tool-based interface that an LLM can call safely. 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 You will need: - A Composio API key - An OpenAI API key (used by Autogen's OpenAIChatCompletionClient) - A Retailed account you can connect to Composio - Some basic familiarity with Autogen and Python async ### 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 Install Composio, Autogen extensions, and dotenv. What's happening: - composio connects your agent to Retailed via MCP - autogen-agentchat provides the AssistantAgent class - autogen-ext-openai provides the OpenAI model client - autogen-ext-tools provides MCP workbench support ```bash pip install composio python-dotenv pip install autogen-agentchat autogen-ext-openai autogen-ext-tools ``` ### 3. Set up environment variables Create a .env file in your project folder. What's happening: - COMPOSIO_API_KEY is required to talk to Composio - OPENAI_API_KEY is used by Autogen's OpenAI client - USER_ID is how Composio identifies which user's Retailed connections to use ```bash COMPOSIO_API_KEY=your-composio-api-key OPENAI_API_KEY=your-openai-api-key USER_ID=your-user-identifier@example.com ``` ### 4. Import dependencies and create Tool Router session What's happening: - load_dotenv() reads your .env file - Composio(api_key=...) initializes the SDK - create(...) creates a Tool Router session that exposes Retailed tools - session.mcp.url is the MCP endpoint that Autogen will connect to ```python import asyncio import os from dotenv import load_dotenv from composio import Composio from autogen_agentchat.agents import AssistantAgent from autogen_ext.models.openai import OpenAIChatCompletionClient from autogen_ext.tools.mcp import McpWorkbench, StreamableHttpServerParams load_dotenv() async def main(): # Initialize Composio and create a Retailed session composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY")) session = composio.create( user_id=os.getenv("USER_ID"), toolkits=["retailed"] ) url = session.mcp.url ``` ### 5. Configure MCP parameters for Autogen Autogen expects parameters describing how to talk to the MCP server. That is what StreamableHttpServerParams is for. What's happening: - url points to the Tool Router MCP endpoint from Composio - timeout is the HTTP timeout for requests - sse_read_timeout controls how long to wait when streaming responses - terminate_on_close=True cleans up the MCP server process when the workbench is closed ```python # Configure MCP server parameters for Streamable HTTP server_params = StreamableHttpServerParams( url=url, timeout=30.0, sse_read_timeout=300.0, terminate_on_close=True, headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")} ) ``` ### 6. Create the model client and agent What's happening: - OpenAIChatCompletionClient wraps the OpenAI model for Autogen - McpWorkbench connects the agent to the MCP tools - AssistantAgent is configured with the Retailed tools from the workbench ```python # Create model client model_client = OpenAIChatCompletionClient( model="gpt-5", api_key=os.getenv("OPENAI_API_KEY") ) # Use McpWorkbench as context manager async with McpWorkbench(server_params) as workbench: # Create Retailed assistant agent with MCP tools agent = AssistantAgent( name="retailed_assistant", description="An AI assistant that helps with Retailed operations.", model_client=model_client, workbench=workbench, model_client_stream=True, max_tool_iterations=10 ) ``` ### 7. Run the interactive chat loop What's happening: - The script prompts you in a loop with You: - Autogen passes your input to the model, which decides which Retailed tools to call via MCP - agent.run_stream(...) yields streaming messages as the agent thinks and calls tools - Typing exit, quit, or bye ends the loop ```python print("Chat started! Type 'exit' or 'quit' to end the conversation.\n") print("Ask any Retailed related question or task to the agent.\n") # Conversation loop while True: user_input = input("You: ").strip() if user_input.lower() in ["exit", "quit", "bye"]: print("\nGoodbye!") break if not user_input: continue print("\nAgent is thinking...\n") # Run the agent with streaming try: response_text = "" async for message in agent.run_stream(task=user_input): if hasattr(message, "content") and message.content: response_text = message.content # Print the final response if response_text: print(f"Agent: {response_text}\n") else: print("Agent: I encountered an issue processing your request.\n") except Exception as e: print(f"Agent: Sorry, I encountered an error: {str(e)}\n") ``` ## Complete Code ```python import asyncio import os from dotenv import load_dotenv from composio import Composio from autogen_agentchat.agents import AssistantAgent from autogen_ext.models.openai import OpenAIChatCompletionClient from autogen_ext.tools.mcp import McpWorkbench, StreamableHttpServerParams load_dotenv() async def main(): # Initialize Composio and create a Retailed session composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY")) session = composio.create( user_id=os.getenv("USER_ID"), toolkits=["retailed"] ) url = session.mcp.url # Configure MCP server parameters for Streamable HTTP server_params = StreamableHttpServerParams( url=url, timeout=30.0, sse_read_timeout=300.0, terminate_on_close=True, headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")} ) # Create model client model_client = OpenAIChatCompletionClient( model="gpt-5", api_key=os.getenv("OPENAI_API_KEY") ) # Use McpWorkbench as context manager async with McpWorkbench(server_params) as workbench: # Create Retailed assistant agent with MCP tools agent = AssistantAgent( name="retailed_assistant", description="An AI assistant that helps with Retailed operations.", model_client=model_client, workbench=workbench, model_client_stream=True, max_tool_iterations=10 ) print("Chat started! Type 'exit' or 'quit' to end the conversation.\n") print("Ask any Retailed related question or task to the agent.\n") # Conversation loop while True: user_input = input("You: ").strip() if user_input.lower() in ['exit', 'quit', 'bye']: print("\nGoodbye!") break if not user_input: continue print("\nAgent is thinking...\n") # Run the agent with streaming try: response_text = "" async for message in agent.run_stream(task=user_input): if hasattr(message, 'content') and message.content: response_text = message.content # Print the final response if response_text: print(f"Agent: {response_text}\n") else: print("Agent: I encountered an issue processing your request.\n") except Exception as e: print(f"Agent: Sorry, I encountered an error: {str(e)}\n") if __name__ == "__main__": asyncio.run(main()) ``` ## Conclusion You now have an Autogen assistant wired into Retailed through Composio's Tool Router and MCP. From here you can: - Add more toolkits to the toolkits list, for example notion or hubspot - Refine the agent description to point it at specific workflows - Wrap this script behind a UI, Slack bot, or internal tool Once the pattern is clear for Retailed, you can reuse the same structure for other MCP-enabled apps with minimal code changes. ## 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) - [CrewAI](https://composio.dev/toolkits/retailed/framework/crew-ai) ## 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 Autogen? Yes, you can. Autogen 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)