# How to integrate Zylvie MCP with CrewAI ```json { "title": "How to integrate Zylvie MCP with CrewAI", "toolkit": "Zylvie", "toolkit_slug": "zylvie", "framework": "CrewAI", "framework_slug": "crew-ai", "url": "https://composio.dev/toolkits/zylvie/framework/crew-ai", "markdown_url": "https://composio.dev/toolkits/zylvie/framework/crew-ai.md", "updated_at": "2026-05-06T08:35:15.299Z" } ``` ## Introduction This guide walks you through connecting Zylvie to CrewAI using the Composio tool router. By the end, you'll have a working Zylvie agent that can add a new digital course product, fetch your current zylvie account profile, remove webhook for subscription cancellations through natural language commands. This guide will help you understand how to give your CrewAI agent real control over a Zylvie account through Composio's Zylvie MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved. ## Also integrate Zylvie with - [OpenAI Agents SDK](https://composio.dev/toolkits/zylvie/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/zylvie/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/zylvie/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/zylvie/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/zylvie/framework/codex) - [OpenClaw](https://composio.dev/toolkits/zylvie/framework/openclaw) - [Hermes](https://composio.dev/toolkits/zylvie/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/zylvie/framework/cli) - [Google ADK](https://composio.dev/toolkits/zylvie/framework/google-adk) - [LangChain](https://composio.dev/toolkits/zylvie/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/zylvie/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/zylvie/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/zylvie/framework/llama-index) ## TL;DR Here's what you'll learn: - Get a Composio API key and configure your Zylvie connection - Set up CrewAI with an MCP enabled agent - Create a Tool Router session or standalone MCP server for Zylvie - Build a conversational loop where your agent can execute Zylvie 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 Zylvie MCP server, and what's possible with it? The Zylvie MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Zylvie account. It provides structured and secure access to your Zylvie workspace, so your agent can perform actions like creating products, managing subscriptions, and retrieving user information on your behalf. - Automated product creation: Instantly add new digital products to your Zylvie store with customizable options, all through natural language prompts to your agent. - User profile retrieval: Quickly fetch details about the currently authenticated user, making it easy to personalize workflows and manage account settings. - Webhook management: Seamlessly unsubscribe from webhooks by deleting workflow objects associated with specific webhook URLs, ensuring your integrations stay clean and up to date. - Subscription and workflow automation: Let your agent help manage ongoing workflows by removing unneeded subscriptions, keeping your sales automations streamlined. ## Supported Tools | Tool slug | Name | Description | |---|---|---| | `ZYLVIE_CREATE_PRODUCT` | Create Product | Tool to create a new product. use when you need to add a product with detailed custom options in zylvie platform. | | `ZYLVIE_GET_AUTHENTICATING_USER` | Get Authenticating User | Tool to retrieve information about the currently authenticated user. use when you have a valid bearer token and need to fetch the authenticated user's profile. | | `ZYLVIE_UNSUBSCRIBE_WEBHOOK` | Unsubscribe Webhook | Tool to unsubscribe from a webhook by deleting the workflow object associated with the specified webhook url. use after confirming the webhook url to remove. | ## Supported Triggers None listed. ## Creating MCP Server - Stand-alone vs Composio SDK The Zylvie MCP server is an implementation of the Model Context Protocol that connects your AI agent to Zylvie. It provides structured and secure access so your agent can perform Zylvie 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 Zylvie 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 Zylvie 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 Zylvie 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 Zylvie **What's happening:** - You create a Zylvie only session through Composio - Composio returns an MCP HTTP URL that exposes Zylvie tools ```python composio_client = Composio(api_key=COMPOSIO_API_KEY) session = composio_client.create(user_id=COMPOSIO_USER_ID, toolkits=["zylvie"]) 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=["zylvie"], ) 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 Zylvie through Composio's Tool Router. The agent can perform Zylvie 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 Zylvie MCP Agent with another framework - [OpenAI Agents SDK](https://composio.dev/toolkits/zylvie/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/zylvie/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/zylvie/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/zylvie/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/zylvie/framework/codex) - [OpenClaw](https://composio.dev/toolkits/zylvie/framework/openclaw) - [Hermes](https://composio.dev/toolkits/zylvie/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/zylvie/framework/cli) - [Google ADK](https://composio.dev/toolkits/zylvie/framework/google-adk) - [LangChain](https://composio.dev/toolkits/zylvie/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/zylvie/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/zylvie/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/zylvie/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 Zylvie MCP? With a standalone Zylvie MCP server, the agents and LLMs can only access a fixed set of Zylvie tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Zylvie 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 Zylvie tools. ### Can I manage the permissions and scopes for Zylvie while using Tool Router? Yes, absolutely. You can configure which Zylvie 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 Zylvie data and credentials are handled as safely as possible. --- [See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)