# How to integrate Goody MCP with Autogen ```json { "title": "How to integrate Goody MCP with Autogen", "toolkit": "Goody", "toolkit_slug": "goody", "framework": "AutoGen", "framework_slug": "autogen", "url": "https://composio.dev/toolkits/goody/framework/autogen", "markdown_url": "https://composio.dev/toolkits/goody/framework/autogen.md", "updated_at": "2026-05-12T10:13:28.948Z" } ``` ## Introduction This guide walks you through connecting Goody to AutoGen using the Composio tool router. By the end, you'll have a working Goody agent that can list all available gift products for birthdays, estimate price for sending 50 gift cards, show your most recent goody orders through natural language commands. This guide will help you understand how to give your AutoGen agent real control over a Goody account through Composio's Goody MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved. ## Also integrate Goody with - [OpenAI Agents SDK](https://composio.dev/toolkits/goody/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/goody/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/goody/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/goody/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/goody/framework/codex) - [OpenClaw](https://composio.dev/toolkits/goody/framework/openclaw) - [Hermes](https://composio.dev/toolkits/goody/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/goody/framework/cli) - [Google ADK](https://composio.dev/toolkits/goody/framework/google-adk) - [LangChain](https://composio.dev/toolkits/goody/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/goody/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/goody/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/goody/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/goody/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 Goody - Wire that MCP URL into Autogen using McpWorkbench and StreamableHttpServerParams - Configure an Autogen AssistantAgent that can call Goody tools - Run a live chat loop where you ask the agent to perform Goody 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 Goody MCP server, and what's possible with it? The Goody MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Goody account. It provides structured and secure access to your gifting and commerce operations, so your agent can perform actions like listing products, calculating order costs, retrieving order details, and managing payment methods on your behalf. - Active product and card discovery: Instantly fetch all available physical products and digital greeting cards to streamline gift selection for any occasion. - Order batch pricing and estimation: Let your agent calculate per-recipient and total costs for a batch order before placing it, making budgeting and planning a breeze. - Order and batch management: Effortlessly retrieve lists of all your orders or order batches, helping you monitor, audit, or report on gifting activity. - Payment methods and workspace management: Quickly access all payment methods and workspaces tied to your account, so your agent can select the right context or handle checkout securely. - User and product detail retrieval: Pull up detailed information on any product or view your current user profile to personalize gifting experiences and account management. ## Supported Tools | Tool slug | Name | Description | |---|---|---| | `GOODY_CALCULATE_PRICE_FOR_ORDER_BATCH` | Calculate Price for Order Batch | Calculate price estimate for an order batch before creation. Returns per-recipient cart pricing (product, shipping, processing, tax) and total batch cost. All prices are in USD cents (e.g., 100 = $1.00). Use this to preview costs before creating an order batch. | | `GOODY_CREATE_WEBHOOK` | Create Webhook | Tool to create a webhook endpoint to receive notifications about order events. Use when you need to set up automated notifications for order lifecycle events like creation, shipment, or delivery. | | `GOODY_DELETE_WEBHOOK` | Delete Webhook | Delete a webhook endpoint to stop receiving notifications from Goody API. Use this when you need to remove a webhook endpoint that is no longer needed or needs to be reconfigured. The operation returns a 204 status code on successful deletion. | | `GOODY_LIST_ALL_ACTIVE_CARDS` | List All Active Cards | Tool to list all active digital greeting cards. Use when you need to fetch available card options before sending. | | `GOODY_LIST_ALL_ACTIVE_PRODUCTS` | List All Active Products | Tool to list all active products. Use when you need to fetch available active products with pagination and filters. | | `GOODY_LIST_ALL_ORDER_BATCHES` | List All Order Batches | Tool to list all order batches. Use when you need to paginate through your account's order batches. | | `GOODY_LIST_ALL_ORDERS` | List All Orders | Retrieves a paginated list of all orders across all order batches in your Goody account. Returns order details including recipient information, cart items, amounts, status, and gift links. Supports pagination with customizable page size (1-100 orders per page). | | `GOODY_LIST_ALL_PAYMENT_METHODS` | List All Payment Methods | Retrieves all saved payment methods for the authenticated account. Payment methods include credit cards and other payment types that can be used when creating orders. No parameters required - simply call this action to get the complete list of payment methods with their IDs, names, and details. | | `GOODY_LIST_ALL_WORKSPACES` | List All Workspaces | Tool to list all workspaces. Use when you need to retrieve all workspaces associated with the account. | | `GOODY_LIST_COLLECTIONS` | List Collections | Tool to list all collections across accessible workspaces. Use when you need to retrieve product collections available in Goody. This endpoint is limited to Automation API usage and returns paginated results. | | `GOODY_LIST_ORDER_ACTIVITIES` | List Order Activities | Tool to list all order activities (events) in your workspace. Returns a paginated list of order status transitions and related events. Use when you need to track order lifecycle events, monitor status changes, or audit order history. | | `GOODY_RETRIEVE_CURRENT_USER` | Retrieve Current User | Retrieve the current authenticated user's profile information from Goody API. This endpoint returns the email and public app ID associated with the authenticated account. Use this to verify authentication status or fetch the current user's account details. No parameters are required - authentication is handled via the Bearer token in headers. | | `GOODY_RETRIEVE_PRODUCT` | Retrieve Product | Tool to retrieve details of a specific product by its ID. Use after obtaining the product ID. | ## Supported Triggers None listed. ## Creating MCP Server - Stand-alone vs Composio SDK The Goody MCP server is an implementation of the Model Context Protocol that connects your AI agents and assistants directly to Goody. Instead of manually wiring Goody 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 Goody 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 Goody 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 Goody 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 Goody 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 Goody session composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY")) session = composio.create( user_id=os.getenv("USER_ID"), toolkits=["goody"] ) 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 Goody 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 Goody assistant agent with MCP tools agent = AssistantAgent( name="goody_assistant", description="An AI assistant that helps with Goody 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 Goody 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 Goody 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 Goody session composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY")) session = composio.create( user_id=os.getenv("USER_ID"), toolkits=["goody"] ) 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 Goody assistant agent with MCP tools agent = AssistantAgent( name="goody_assistant", description="An AI assistant that helps with Goody 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 Goody 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 Goody 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 Goody, you can reuse the same structure for other MCP-enabled apps with minimal code changes. ## How to build Goody MCP Agent with another framework - [OpenAI Agents SDK](https://composio.dev/toolkits/goody/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/goody/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/goody/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/goody/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/goody/framework/codex) - [OpenClaw](https://composio.dev/toolkits/goody/framework/openclaw) - [Hermes](https://composio.dev/toolkits/goody/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/goody/framework/cli) - [Google ADK](https://composio.dev/toolkits/goody/framework/google-adk) - [LangChain](https://composio.dev/toolkits/goody/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/goody/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/goody/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/goody/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/goody/framework/crew-ai) ## Related Toolkits - [Addresszen](https://composio.dev/toolkits/addresszen) - Addresszen is a real-time address autocomplete and verification service. 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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. 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It streamlines promotions and gift card transactions for businesses and their customers. - [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 Goody MCP? With a standalone Goody MCP server, the agents and LLMs can only access a fixed set of Goody tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Goody 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 Goody tools. ### Can I manage the permissions and scopes for Goody while using Tool Router? Yes, absolutely. You can configure which Goody 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 Goody data and credentials are handled as safely as possible. --- [See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)