# How to integrate Zixflow MCP with Mastra AI

```json
{
  "title": "How to integrate Zixflow MCP with Mastra AI",
  "toolkit": "Zixflow",
  "toolkit_slug": "zixflow",
  "framework": "Mastra AI",
  "framework_slug": "mastra-ai",
  "url": "https://composio.dev/toolkits/zixflow/framework/mastra-ai",
  "markdown_url": "https://composio.dev/toolkits/zixflow/framework/mastra-ai.md",
  "updated_at": "2026-03-29T06:56:25.114Z"
}
```

## Introduction

This guide walks you through connecting Zixflow to Mastra 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 Mastra 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)
- [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:
- Set up your environment so Mastra, OpenAI, and Composio work together
- Create a Tool Router session in Composio that exposes Zixflow tools
- Connect Mastra's MCP client to the Composio generated MCP URL
- Fetch Zixflow tool definitions and attach them as a toolset
- Build a Mastra agent that can reason, call tools, and return structured results
- Run an interactive CLI where you can chat with your Zixflow agent

## What is Mastra AI?

Mastra AI is a TypeScript framework for building AI agents with tool support. It provides a clean API for creating agents that can use external services through MCP.
Key features include:
- MCP Client: Built-in support for Model Context Protocol servers
- Toolsets: Organize tools into logical groups
- Step Callbacks: Monitor and debug agent execution
- OpenAI Integration: Works with OpenAI models via @ai-sdk/openai

## 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:
- Node.js 18 or higher
- A Composio account with an active API key
- An OpenAI API key
- Basic familiarity with TypeScript

### 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 need credits or a connected billing setup to use the models.
- Store the key somewhere safe.
Composio API Key
- Log in to the [Composio dashboard](https://dashboard.composio.dev?utm_source=toolkits&utm_medium=framework_docs).
- Go to Settings and copy your API key.
- This key lets your Mastra agent talk to Composio and reach Zixflow through MCP.

### 2. Install dependencies

Install the required packages.
What's happening:
- @composio/core is the Composio SDK for creating MCP sessions
- @mastra/core provides the Agent class
- @mastra/mcp is Mastra's MCP client
- @ai-sdk/openai is the model wrapper for OpenAI
- dotenv loads environment variables from .env
```bash
npm install @composio/core @mastra/core @mastra/mcp @ai-sdk/openai dotenv
```

### 3. Set up environment variables

Create a .env file in your project root.
What's happening:
- COMPOSIO_API_KEY authenticates your requests to Composio
- COMPOSIO_USER_ID tells Composio which user this session belongs to
- OPENAI_API_KEY lets the Mastra agent call OpenAI models
```bash
COMPOSIO_API_KEY=your_composio_api_key_here
COMPOSIO_USER_ID=your_user_id_here
OPENAI_API_KEY=your_openai_api_key_here
```

### 4. Import libraries and validate environment

What's happening:
- dotenv/config auto loads your .env so process.env.* is available
- openai gives you a Mastra compatible model wrapper
- Agent is the Mastra agent that will call tools and produce answers
- MCPClient connects Mastra to your Composio MCP server
- Composio is used to create a Tool Router session
```typescript
import "dotenv/config";
import { openai } from "@ai-sdk/openai";
import { Agent } from "@mastra/core/agent";
import { MCPClient } from "@mastra/mcp";
import { Composio } from "@composio/core";
import * as readline from "readline";

import type { AiMessageType } from "@mastra/core/agent";

const openaiAPIKey = process.env.OPENAI_API_KEY;
const composioAPIKey = process.env.COMPOSIO_API_KEY;
const composioUserID = process.env.COMPOSIO_USER_ID;

if (!openaiAPIKey) throw new Error("OPENAI_API_KEY is not set");
if (!composioAPIKey) throw new Error("COMPOSIO_API_KEY is not set");
if (!composioUserID) throw new Error("COMPOSIO_USER_ID is not set");

const composio = new Composio({
  apiKey: composioAPIKey as string,
});
```

### 5. Create a Tool Router session for Zixflow

What's happening:
- create spins up a short-lived MCP HTTP endpoint for this user
- The toolkits array contains "zixflow" for Zixflow access
- session.mcp.url is the MCP URL that Mastra's MCPClient will connect to
```typescript
async function main() {
  const session = await composio.create(
    composioUserID as string,
    {
      toolkits: ["zixflow"],
    },
  );

  const composioMCPUrl = session.mcp.url;
  console.log("Zixflow MCP URL:", composioMCPUrl);
```

### 6. Configure Mastra MCP client and fetch tools

What's happening:
- MCPClient takes an id for this client and a list of MCP servers
- The headers property includes the x-api-key for authentication
- getTools fetches the tool definitions exposed by the Zixflow toolkit
```typescript
const mcpClient = new MCPClient({
    id: composioUserID as string,
    servers: {
      nasdaq: {
        url: new URL(composioMCPUrl),
        requestInit: {
          headers: session.mcp.headers,
        },
      },
    },
    timeout: 30_000,
  });

console.log("Fetching MCP tools from Composio...");
const composioTools = await mcpClient.getTools();
console.log("Number of tools:", Object.keys(composioTools).length);
```

### 7. Create the Mastra agent

What's happening:
- Agent is the core Mastra agent
- name is just an identifier for logging and debugging
- instructions guide the agent to use tools instead of only answering in natural language
- model uses openai("gpt-5") to configure the underlying LLM
```typescript
const agent = new Agent({
    name: "zixflow-mastra-agent",
    instructions: "You are an AI agent with Zixflow tools via Composio.",
    model: "openai/gpt-5",
  });
```

### 8. Set up interactive chat interface

What's happening:
- messages keeps the full conversation history in Mastra's expected format
- agent.generate runs the agent with conversation history and Zixflow toolsets
- maxSteps limits how many tool calls the agent can take in a single run
- onStepFinish is a hook that prints intermediate steps for debugging
```typescript
let messages: AiMessageType[] = [];

console.log("Chat started! Type 'exit' or 'quit' to end.\n");

const rl = readline.createInterface({
  input: process.stdin,
  output: process.stdout,
  prompt: "> ",
});

rl.prompt();

rl.on("line", async (userInput: string) => {
  const trimmedInput = userInput.trim();

  if (["exit", "quit", "bye"].includes(trimmedInput.toLowerCase())) {
    console.log("\nGoodbye!");
    rl.close();
    process.exit(0);
  }

  if (!trimmedInput) {
    rl.prompt();
    return;
  }

  messages.push({
    id: crypto.randomUUID(),
    role: "user",
    content: trimmedInput,
  });

  console.log("\nAgent is thinking...\n");

  try {
    const response = await agent.generate(messages, {
      toolsets: {
        zixflow: composioTools,
      },
      maxSteps: 8,
    });

    const { text } = response;

    if (text && text.trim().length > 0) {
      console.log(`Agent: ${text}\n`);
        messages.push({
          id: crypto.randomUUID(),
          role: "assistant",
          content: text,
        });
      }
    } catch (error) {
      console.error("\nError:", error);
    }

    rl.prompt();
  });

  rl.on("close", async () => {
    console.log("\nSession ended.");
    await mcpClient.disconnect();
    process.exit(0);
  });
}

main().catch((err) => {
  console.error("Fatal error:", err);
  process.exit(1);
});
```

## Complete Code

```typescript
import "dotenv/config";
import { openai } from "@ai-sdk/openai";
import { Agent } from "@mastra/core/agent";
import { MCPClient } from "@mastra/mcp";
import { Composio } from "@composio/core";
import * as readline from "readline";

import type { AiMessageType } from "@mastra/core/agent";

const openaiAPIKey = process.env.OPENAI_API_KEY;
const composioAPIKey = process.env.COMPOSIO_API_KEY;
const composioUserID = process.env.COMPOSIO_USER_ID;

if (!openaiAPIKey) throw new Error("OPENAI_API_KEY is not set");
if (!composioAPIKey) throw new Error("COMPOSIO_API_KEY is not set");
if (!composioUserID) throw new Error("COMPOSIO_USER_ID is not set");

const composio = new Composio({ apiKey: composioAPIKey as string });

async function main() {
  const session = await composio.create(composioUserID as string, {
    toolkits: ["zixflow"],
  });

  const composioMCPUrl = session.mcp.url;

  const mcpClient = new MCPClient({
    id: composioUserID as string,
    servers: {
      zixflow: {
        url: new URL(composioMCPUrl),
        requestInit: {
          headers: session.mcp.headers,
        },
      },
    },
    timeout: 30_000,
  });

  const composioTools = await mcpClient.getTools();

  const agent = new Agent({
    name: "zixflow-mastra-agent",
    instructions: "You are an AI agent with Zixflow tools via Composio.",
    model: "openai/gpt-5",
  });

  let messages: AiMessageType[] = [];

  const rl = readline.createInterface({
    input: process.stdin,
    output: process.stdout,
    prompt: "> ",
  });

  rl.prompt();

  rl.on("line", async (input: string) => {
    const trimmed = input.trim();
    if (["exit", "quit"].includes(trimmed.toLowerCase())) {
      rl.close();
      return;
    }

    messages.push({ id: crypto.randomUUID(), role: "user", content: trimmed });

    const { text } = await agent.generate(messages, {
      toolsets: { zixflow: composioTools },
      maxSteps: 8,
    });

    if (text) {
      console.log(`Agent: ${text}\n`);
      messages.push({ id: crypto.randomUUID(), role: "assistant", content: text });
    }

    rl.prompt();
  });

  rl.on("close", async () => {
    await mcpClient.disconnect();
    process.exit(0);
  });
}

main();
```

## Conclusion

You've built a Mastra AI agent that can interact with Zixflow through Composio's Tool Router.
You can extend this further by:
- Adding other toolkits like Gmail, Slack, or GitHub
- Building a web-based chat interface around this agent
- Using multiple MCP endpoints to enable cross-app workflows

## 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)
- [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 Mastra AI?

Yes, you can. Mastra 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)
