# How to integrate Zixflow MCP with Pydantic AI ```json { "title": "How to integrate Zixflow MCP with Pydantic AI", "toolkit": "Zixflow", "toolkit_slug": "zixflow", "framework": "Pydantic AI", "framework_slug": "pydantic-ai", "url": "https://composio.dev/toolkits/zixflow/framework/pydantic-ai", "markdown_url": "https://composio.dev/toolkits/zixflow/framework/pydantic-ai.md", "updated_at": "2026-03-29T06:56:25.114Z" } ``` ## Introduction This guide walks you through connecting Zixflow to Pydantic AI using the Composio tool router. By the end, you'll have a working Zixflow agent that can send a bulk sms campaign to all new leads, add a follow-up reminder for every hot lead, list conversations from whatsapp with unread responses through natural language commands. This guide will help you understand how to give your Pydantic AI agent real control over a Zixflow account through Composio's Zixflow MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved. ## Also integrate Zixflow with - [OpenAI Agents SDK](https://composio.dev/toolkits/zixflow/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/zixflow/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/zixflow/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/zixflow/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/zixflow/framework/codex) - [OpenClaw](https://composio.dev/toolkits/zixflow/framework/openclaw) - [Hermes](https://composio.dev/toolkits/zixflow/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/zixflow/framework/cli) - [Google ADK](https://composio.dev/toolkits/zixflow/framework/google-adk) - [LangChain](https://composio.dev/toolkits/zixflow/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/zixflow/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/zixflow/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/zixflow/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/zixflow/framework/crew-ai) ## TL;DR Here's what you'll learn: - How to set up your Composio API key and User ID - How to create a Composio Tool Router session for Zixflow - How to attach an MCP Server to a Pydantic AI agent - How to stream responses and maintain chat history - How to build a simple REPL-style chat interface to test your Zixflow workflows ## What is Pydantic AI? Pydantic AI is a Python framework for building AI agents with strong typing and validation. It leverages Pydantic's data validation capabilities to create robust, type-safe AI applications. Key features include: - Type Safety: Built on Pydantic for automatic data validation - MCP Support: Native support for Model Context Protocol servers - Streaming: Built-in support for streaming responses - Async First: Designed for async/await patterns ## What is the Zixflow MCP server, and what's possible with it? The Zixflow MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Zixflow account. It provides structured and secure access so your agent can perform Zixflow operations on your behalf. ## Supported Tools | Tool slug | Name | Description | |---|---|---| | `ZIXFLOW_CREATE_ATTRIBUTE` | Create Attribute | Tool to create a custom attribute for a Zixflow collection or list. Use when you need to add new fields to track specific data types (text, number, email, etc.). Attributes define the structure of your data. Common use cases: adding custom fields for contacts, creating status trackers, adding reference fields between collections. | | `ZIXFLOW_GET_CAMPAIGN_REPORT_WHATSAPP` | Get WhatsApp Campaign Report | Tool to retrieve WhatsApp campaign message report. Use when you need to check the delivery status and details of a WhatsApp message sent via campaign. | | `ZIXFLOW_GET_EMAIL_REPORT` | Get Email Report | Tool to retrieve email message delivery report from Zixflow. Use when you need to check the delivery status of a sent campaign email. The report includes delivery status (SENT, OPENED, CLICKED, BOUNCE, COMPLAINT, UNSUBSCRIBED), recipient information, and timestamps. Requires the message ID obtained when sending the campaign. | | `ZIXFLOW_GET_SMS_REPORT` | Get SMS Report | Tool to retrieve SMS message delivery report from Zixflow. Use when you need to check the delivery status, destination, and other details of a sent SMS campaign message. | | `ZIXFLOW_GET_WHATSAPP_TEMPLATE_VARIABLES` | Get WhatsApp Template Variables | Tool to retrieve template variable details for a WhatsApp template. Use when you need to understand what variables a specific WhatsApp template expects before sending a message. | | `ZIXFLOW_LIST_ATTRIBUTE_OPTIONS` | List Attribute Options | Tool to retrieve the list of options for select/multiselect attributes. Use when you need to get available options for a specific attribute in a collection or list. | | `ZIXFLOW_LIST_ATTRIBUTE_STATUS_OPTIONS` | List Attribute Status Options | Tool to retrieve the list of options for status attributes in Zixflow. Use when you need to fetch available status configurations for a specific attribute within a collection or list. | ## Supported Triggers None listed. ## Creating MCP Server - Stand-alone vs Composio SDK The Zixflow MCP server is an implementation of the Model Context Protocol that connects your AI agent to Zixflow. It provides structured and secure access so your agent can perform Zixflow 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 with an active API key - Basic familiarity with Python and async programming ### 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 the required libraries. What's happening: - composio connects your agent to external SaaS tools like Zixflow - pydantic-ai lets you create structured AI agents with tool support - python-dotenv loads your environment variables securely from a .env file ```bash pip install composio pydantic-ai python-dotenv ``` ### 3. Set up environment variables Create a .env file in your project root. What's happening: - COMPOSIO_API_KEY authenticates your agent to Composio's API - USER_ID associates your session with your account for secure tool access - OPENAI_API_KEY to access OpenAI LLMs ```bash COMPOSIO_API_KEY=your_composio_api_key_here USER_ID=your_user_id_here OPENAI_API_KEY=your_openai_api_key ``` ### 4. Import dependencies What's happening: - We load environment variables and import required modules - Composio manages connections to Zixflow - MCPServerStreamableHTTP connects to the Zixflow MCP server endpoint - Agent from Pydantic AI lets you define and run the AI assistant ```python import asyncio import os from dotenv import load_dotenv from composio import Composio from pydantic_ai import Agent from pydantic_ai.mcp import MCPServerStreamableHTTP load_dotenv() ``` ### 5. Create a Tool Router Session What's happening: - We're creating a Tool Router session that gives your agent access to Zixflow tools - The create method takes the user ID and specifies which toolkits should be available - The returned session.mcp.url is the MCP server URL that your agent will use ```python async def main(): api_key = os.getenv("COMPOSIO_API_KEY") user_id = os.getenv("USER_ID") if not api_key or not user_id: raise RuntimeError("Set COMPOSIO_API_KEY and USER_ID in your environment") # Create a Composio Tool Router session for Zixflow composio = Composio(api_key=api_key) session = composio.create( user_id=user_id, toolkits=["zixflow"], ) url = session.mcp.url if not url: raise ValueError("Composio session did not return an MCP URL") ``` ### 6. Initialize the Pydantic AI Agent What's happening: - The MCP client connects to the Zixflow endpoint - The agent uses GPT-5 to interpret user commands and perform Zixflow operations - The instructions field defines the agent's role and behavior ```python # Attach the MCP server to a Pydantic AI Agent zixflow_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY}) agent = Agent( "openai:gpt-5", toolsets=[zixflow_mcp], instructions=( "You are a Zixflow assistant. Use Zixflow tools to help users " "with their requests. Ask clarifying questions when needed." ), ) ``` ### 7. Build the chat interface What's happening: - The agent reads input from the terminal and streams its response - Zixflow API calls happen automatically under the hood - The model keeps conversation history to maintain context across turns ```python # Simple REPL with message history history = [] print("Chat started! Type 'exit' or 'quit' to end.\n") print("Try asking the agent to help you with Zixflow.\n") 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", flush=True) async with agent.run_stream(user_input, message_history=history) as stream_result: collected_text = "" async for chunk in stream_result.stream_output(): text_piece = None if isinstance(chunk, str): text_piece = chunk elif hasattr(chunk, "delta") and isinstance(chunk.delta, str): text_piece = chunk.delta elif hasattr(chunk, "text"): text_piece = chunk.text if text_piece: collected_text += text_piece result = stream_result print(f"Agent: {collected_text}\n") history = result.all_messages() ``` ### 8. Run the application What's happening: - The asyncio loop launches the agent and keeps it running until you exit ```python if __name__ == "__main__": asyncio.run(main()) ``` ## Complete Code ```python import asyncio import os from dotenv import load_dotenv from composio import Composio from pydantic_ai import Agent from pydantic_ai.mcp import MCPServerStreamableHTTP load_dotenv() async def main(): api_key = os.getenv("COMPOSIO_API_KEY") user_id = os.getenv("USER_ID") if not api_key or not user_id: raise RuntimeError("Set COMPOSIO_API_KEY and USER_ID in your environment") # Create a Composio Tool Router session for Zixflow composio = Composio(api_key=api_key) session = composio.create( user_id=user_id, toolkits=["zixflow"], ) url = session.mcp.url if not url: raise ValueError("Composio session did not return an MCP URL") # Attach the MCP server to a Pydantic AI Agent zixflow_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY}) agent = Agent( "openai:gpt-5", toolsets=[zixflow_mcp], instructions=( "You are a Zixflow assistant. Use Zixflow tools to help users " "with their requests. Ask clarifying questions when needed." ), ) # Simple REPL with message history history = [] print("Chat started! Type 'exit' or 'quit' to end.\n") print("Try asking the agent to help you with Zixflow.\n") 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", flush=True) async with agent.run_stream(user_input, message_history=history) as stream_result: collected_text = "" async for chunk in stream_result.stream_output(): text_piece = None if isinstance(chunk, str): text_piece = chunk elif hasattr(chunk, "delta") and isinstance(chunk.delta, str): text_piece = chunk.delta elif hasattr(chunk, "text"): text_piece = chunk.text if text_piece: collected_text += text_piece result = stream_result print(f"Agent: {collected_text}\n") history = result.all_messages() if __name__ == "__main__": asyncio.run(main()) ``` ## Conclusion You've built a Pydantic AI agent that can interact with Zixflow through Composio's Tool Router. With this setup, your agent can perform real Zixflow actions through natural language. You can extend this further by: - Adding other toolkits like Gmail, HubSpot, or Salesforce - Building a web-based chat interface around this agent - Using multiple MCP endpoints to enable cross-app workflows (for example, Gmail + Zixflow for workflow automation) This architecture makes your AI agent "agent-native", able to securely use APIs in a unified, composable way without custom integrations. ## How to build Zixflow MCP Agent with another framework - [OpenAI Agents SDK](https://composio.dev/toolkits/zixflow/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/zixflow/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/zixflow/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/zixflow/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/zixflow/framework/codex) - [OpenClaw](https://composio.dev/toolkits/zixflow/framework/openclaw) - [Hermes](https://composio.dev/toolkits/zixflow/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/zixflow/framework/cli) - [Google ADK](https://composio.dev/toolkits/zixflow/framework/google-adk) - [LangChain](https://composio.dev/toolkits/zixflow/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/zixflow/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/zixflow/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/zixflow/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/zixflow/framework/crew-ai) ## Related Toolkits - [Google Sheets](https://composio.dev/toolkits/googlesheets) - Google Sheets is a cloud-based spreadsheet tool for real-time collaboration and data analysis. It lets teams work together from anywhere, updating information instantly. - [Notion](https://composio.dev/toolkits/notion) - Notion is a collaborative workspace for notes, docs, wikis, and tasks. It streamlines team knowledge, project tracking, and workflow customization in one place. - [Airtable](https://composio.dev/toolkits/airtable) - Airtable combines the flexibility of spreadsheets with the power of a database for easy project and data management. Teams use Airtable to organize, track, and collaborate with custom views and automations. - [Hubspot](https://composio.dev/toolkits/hubspot) - HubSpot is an all-in-one marketing, sales, and customer service platform. It lets teams nurture leads, automate outreach, and track every customer interaction in one place. - [Asana](https://composio.dev/toolkits/asana) - Asana is a collaborative work management platform for teams to organize and track projects. It streamlines teamwork, boosts productivity, and keeps everyone aligned on goals. - [Pipedrive](https://composio.dev/toolkits/pipedrive) - Pipedrive is a sales management platform offering pipeline visualization, lead tracking, and workflow automation. It helps sales teams keep deals moving forward efficiently and never miss a follow-up. - [Google Tasks](https://composio.dev/toolkits/googletasks) - Google Tasks is a to-do list and task management tool integrated into Gmail and Google Calendar. It helps you organize, track, and complete tasks across your Google ecosystem. - [Linear](https://composio.dev/toolkits/linear) - Linear is a modern issue tracking and project planning tool for fast-moving teams. It helps streamline workflows, organize projects, and boost productivity. - [Salesforce](https://composio.dev/toolkits/salesforce) - Salesforce is a leading CRM platform that helps businesses manage sales, service, and marketing. It centralizes customer data, enabling teams to drive growth and build strong relationships. - [Jira](https://composio.dev/toolkits/jira) - Jira is Atlassian’s platform for bug tracking, issue tracking, and agile project management. It helps teams organize work, prioritize tasks, and deliver projects efficiently. - [Clickup](https://composio.dev/toolkits/clickup) - ClickUp is an all-in-one productivity platform for managing tasks, docs, goals, and team collaboration. It streamlines project workflows so teams can work smarter and stay organized in one place. - [Monday](https://composio.dev/toolkits/monday) - Monday.com is a customizable work management platform for project planning and collaboration. It helps teams organize tasks, automate workflows, and track progress in real time. - [Reddit](https://composio.dev/toolkits/reddit) - Reddit is a social news platform with thriving user-driven communities (subreddits). It's the go-to place for discussion, content sharing, and viral marketing. - [Apollo](https://composio.dev/toolkits/apollo) - Apollo is a CRM and lead generation platform that helps businesses discover contacts and manage sales pipelines. Use it to streamline customer outreach and track your deals from one place. - [Attio](https://composio.dev/toolkits/attio) - Attio is a customizable CRM and workspace for managing your team's relationships and workflows. It helps teams organize contacts, automate tasks, and collaborate more efficiently. - [Facebook](https://composio.dev/toolkits/facebook) - Facebook is a social media and advertising platform for businesses and creators. It helps you connect, share, and manage content across your public Facebook Pages. - [Linkedin](https://composio.dev/toolkits/linkedin) - LinkedIn is a professional networking platform for connecting, sharing content, and engaging with business opportunities. It's the go-to place for building your professional brand and unlocking new career connections. - [Acculynx](https://composio.dev/toolkits/acculynx) - AccuLynx is a cloud-based roofing business management software for contractors. It streamlines project tracking, lead management, and document sharing. - [Active campaign](https://composio.dev/toolkits/active_campaign) - ActiveCampaign is a marketing automation and CRM platform for managing email campaigns, sales pipelines, and customer segmentation. It helps businesses engage customers and drive growth through smart automation and targeted outreach. - [ActiveTrail](https://composio.dev/toolkits/active_trail) - ActiveTrail is a user-friendly email marketing and automation platform. It helps you reach subscribers and automate campaigns with ease. ## Frequently Asked Questions ### What are the differences in Tool Router MCP and Zixflow MCP? With a standalone Zixflow MCP server, the agents and LLMs can only access a fixed set of Zixflow tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Zixflow and many other apps based on the task at hand, all through a single MCP endpoint. ### Can I use Tool Router MCP with Pydantic AI? Yes, you can. Pydantic AI 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 Zixflow tools. ### Can I manage the permissions and scopes for Zixflow while using Tool Router? Yes, absolutely. You can configure which Zixflow 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 Zixflow data and credentials are handled as safely as possible. --- [See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)