How to integrate Iterable MCP with Vercel AI SDK v6

This guide walks you through connecting Iterable to Vercel AI SDK v6 using the Composio tool router. By the end, you'll have a working Iterable agent that can summarize iterable campaign performance today, add customer to welcome journey, update user email subscription status through natural language commands. This guide will help you understand how to give your Vercel AI SDK agent real control over a Iterable account through Composio's Iterable MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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Iterable

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Iterable is a cross-channel marketing platform for building campaigns across email, SMS, push, and in-app channels. It helps teams personalize customer journeys and optimize engagement from one place.

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Introduction

This guide will help you understand how to give your Vercel AI SDK agent real control over a Iterable account through Composio's Iterable MCP server.

Before we dive in, let's take a quick look at the key ideas and tools involved.

Also integrate Iterable with

OpenAI Agents SDK Claude Agent SDK Claude Code Claude Cowork Codex OpenClaw Hermes CLI Google ADK LangChain Mastra AI LlamaIndex CrewAI

TL;DR

Here's what you'll learn:

How to set up and configure a Vercel AI SDK agent with Iterable integration
Using Composio's Tool Router to dynamically load and access Iterable tools
Creating an MCP client connection using HTTP transport
Building an interactive CLI chat interface with conversation history management
Handling tool calls and results within the Vercel AI SDK framework

What is Vercel AI SDK?

The Vercel AI SDK is a TypeScript library for building AI-powered applications. It provides tools for creating agents that can use external services and maintain conversation state.

Key features include:

streamText: Core function for streaming responses with real-time tool support
MCP Client: Built-in support for Model Context Protocol via @ai-sdk/mcp
Step Counting: Control multi-step tool execution with stopWhen: stepCountIs()
OpenAI Provider: Native integration with OpenAI models

What is the Iterable MCP server, and what's possible with it?

The Iterable MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Iterable account. It provides structured and secure access to your campaigns, users, catalogs, templates, messages, and analytics, so your agent can create campaigns, manage audiences, update catalogs, control messages, and review performance on your behalf.

Campaign creation and control: Have your agent create campaigns from existing templates, activate or deactivate triggered campaigns, cancel scheduled campaigns, archive campaigns, or stop campaigns already running.
User and audience management: Let the agent create static lists, update users in bulk, export user events, delete users, or remove a person’s data and prevent future collection.
Catalog and content management: Direct your agent to create catalogs, add or update catalog items, inspect catalog content and field mappings, and remove items or entire catalogs.
Message and template operations: Instruct your agent to review email, in-app, and embedded message templates, create reusable snippets, list message types, and cancel scheduled email, push, web push, in-app, or WhatsApp messages.
Campaign reporting and exports: Have your agent retrieve campaign and experiment metrics, then export campaign analytics in CSV or JSON format for further analysis.

What is the Composio tool router, and how does it fit here?

What is Composio SDK?

Composio's Composio SDK helps agents find the right tools for a task at runtime. You can plug in multiple toolkits (like Gmail, HubSpot, and GitHub), and the agent will identify the relevant app and action to complete multi-step workflows. This can reduce token usage and improve the reliability of tool calls. Read more here: Getting started with Composio SDK

The tool router generates a secure MCP URL that your agents can access to perform actions.

How the Composio SDK works

The Composio SDK follows a three-phase workflow:

Discovery: Searches for tools matching your task and returns relevant toolkits with their details.
Authentication: Checks for active connections. If missing, creates an auth config and returns a connection URL via Auth Link.
Execution: Executes the action using the authenticated connection.

Step-by-step Guide

Step by step09 STEPS

Prerequisites

Before you begin, make sure you have:

Node.js and npm installed
A Composio account with API key
An OpenAI API key

Getting API Keys for OpenAI and Composio

OpenAI API Key

Go to the OpenAI dashboard 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.
Navigate to your API settings and generate a new API key.
Store this key securely as you'll need it for authentication.

Install required dependencies

bash

npm install @ai-sdk/openai @ai-sdk/mcp @composio/core ai dotenv

First, install the necessary packages for your project.

What you're installing:

@ai-sdk/openai: Vercel AI SDK's OpenAI provider
@ai-sdk/mcp: MCP client for Vercel AI SDK
@composio/core: Composio SDK for tool integration
ai: Core Vercel AI SDK
dotenv: Environment variable management

Set up environment variables

bash

OPENAI_API_KEY=your_openai_api_key_here
COMPOSIO_API_KEY=your_composio_api_key_here
COMPOSIO_USER_ID=your_user_id_here

Create a .env file in your project root.

What's needed:

OPENAI_API_KEY: Your OpenAI API key for GPT model access
COMPOSIO_API_KEY: Your Composio API key for tool access
COMPOSIO_USER_ID: A unique identifier for the user session

Import required modules and validate environment

typescript

import "dotenv/config";
import { openai } from "@ai-sdk/openai";
import { Composio } from "@composio/core";
import * as readline from "readline";
import { streamText, type ModelMessage, stepCountIs } from "ai";
import { createMCPClient } from "@ai-sdk/mcp";

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

if (!process.env.OPENAI_API_KEY) 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,
});

What's happening:

We're importing all necessary libraries including Vercel AI SDK's OpenAI provider and Composio
The dotenv/config import automatically loads environment variables
The MCP client import enables connection to Composio's tool server

Create Tool Router session and initialize MCP client

typescript

async function main() {
  // Create a tool router session for the user
  const session = await composio.create(composioUserID!, {
    toolkits: ["iterable"],
  });

  const mcpUrl = session.mcp.url;

What's happening:

We're creating a Tool Router session that gives your agent access to Iterable tools
The create method takes the user ID and specifies which toolkits should be available
The returned mcp object contains the URL and authentication headers needed to connect to the MCP server
This session provides access to all Iterable-related tools through the MCP protocol

Connect to MCP server and retrieve tools

typescript

const mcpClient = await createMCPClient({
  transport: {
    type: "http",
    url: mcpUrl,
    headers: session.mcp.headers, // Authentication headers for the Composio MCP server
  },
});

const tools = await mcpClient.tools();

What's happening:

We're creating an MCP client that connects to our Composio Tool Router session via HTTP
The mcp.url provides the endpoint, and mcp.headers contains authentication credentials
The type: "http" is important - Composio requires HTTP transport
tools() retrieves all available Iterable tools that the agent can use

Initialize conversation and CLI interface

typescript

let messages: ModelMessage[] = [];

console.log("Chat started! Type 'exit' or 'quit' to end the conversation.\n");
console.log(
  "Ask any questions related to iterable, like summarize my last 5 emails, send an email, etc... :)))\n",
);

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

rl.prompt();

What's happening:

We initialize an empty messages array to maintain conversation history
A readline interface is created to accept user input from the command line
Instructions are displayed to guide the user on how to interact with the agent

Handle user input and stream responses with real-time tool feedback

typescript

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({ role: "user", content: trimmedInput });
  console.log("\nAgent is thinking...\n");

  try {
    const stream = streamText({
      model: openai("gpt-5"),
      messages,
      tools,
      toolChoice: "auto",
      stopWhen: stepCountIs(10),
      onStepFinish: (step) => {
        for (const toolCall of step.toolCalls) {
          console.log(`[Using tool: ${toolCall.toolName}]`);
          }
          if (step.toolCalls.length > 0) {
            console.log(""); // Add space after tool calls
          }
        },
      });

      for await (const chunk of stream.textStream) {
        process.stdout.write(chunk);
      }

      console.log("\n\n---\n");

      // Get final result for message history
      const response = await stream.response;
      if (response?.messages?.length) {
        messages.push(...response.messages);
      }
    } catch (error) {
      console.error("\nAn error occurred while talking to the agent:");
      console.error(error);
      console.log(
        "\nYou can try again or restart the app if it keeps happening.\n",
      );
    } finally {
      rl.prompt();
    }
  });

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

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

What's happening:

We use streamText instead of generateText to stream responses in real-time
toolChoice: "auto" allows the model to decide when to use Iterable tools
stopWhen: stepCountIs(10) allows up to 10 steps for complex multi-tool operations
onStepFinish callback displays which tools are being used in real-time
We iterate through the text stream to create a typewriter effect as the agent responds
The complete response is added to conversation history to maintain context
Errors are caught and displayed with helpful retry suggestions

Complete Code

Here's the complete code to get you started with Iterable and Vercel AI SDK:

typescript

import "dotenv/config";
import { openai } from "@ai-sdk/openai";
import { Composio } from "@composio/core";
import * as readline from "readline";
import { streamText, type ModelMessage, stepCountIs } from "ai";
import { createMCPClient } from "@ai-sdk/mcp";

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

if (!process.env.OPENAI_API_KEY) 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,
});

async function main() {
  // Create a tool router session for the user
  const session = await composio.create(composioUserID!, {
    toolkits: ["iterable"],
  });

  const mcpUrl = session.mcp.url;

  const mcpClient = await createMCPClient({
    transport: {
      type: "http",
      url: mcpUrl,
      headers: session.mcp.headers, // Authentication headers for the Composio MCP server
    },
  });

  const tools = await mcpClient.tools();

  let messages: ModelMessage[] = [];

  console.log("Chat started! Type 'exit' or 'quit' to end the conversation.\n");
  console.log(
    "Ask any questions related to iterable, like summarize my last 5 emails, send an email, etc... :)))\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({ role: "user", content: trimmedInput });
    console.log("\nAgent is thinking...\n");

    try {
      const stream = streamText({
        model: openai("gpt-5"),
        messages,
        tools,
        toolChoice: "auto",
        stopWhen: stepCountIs(10),
        onStepFinish: (step) => {
          for (const toolCall of step.toolCalls) {
            console.log(`[Using tool: ${toolCall.toolName}]`);
          }
          if (step.toolCalls.length > 0) {
            console.log(""); // Add space after tool calls
          }
        },
      });

      for await (const chunk of stream.textStream) {
        process.stdout.write(chunk);
      }

      console.log("\n\n---\n");

      // Get final result for message history
      const response = await stream.response;
      if (response?.messages?.length) {
        messages.push(...response.messages);
      }
    } catch (error) {
      console.error("\nAn error occurred while talking to the agent:");
      console.error(error);
      console.log(
        "\nYou can try again or restart the app if it keeps happening.\n",
      );
    } finally {
      rl.prompt();
    }
  });

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

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

Conclusion

You've successfully built a Iterable agent using the Vercel AI SDK with streaming capabilities! This implementation provides a powerful foundation for building AI applications with natural language interfaces and real-time feedback.

Key features of this implementation:

Real-time streaming responses for a better user experience with typewriter effect
Live tool execution feedback showing which tools are being used as the agent works
Dynamic tool loading through Composio's Tool Router with secure authentication
Multi-step tool execution with configurable step limits (up to 10 steps)
Comprehensive error handling for robust agent execution
Conversation history maintenance for context-aware responses

You can extend this further by adding custom error handling, implementing specific business logic, or integrating additional Composio toolkits to create multi-app workflows.

TOOLS

Supported Tools

Every Iterable action and event your agent gets out of the box.

Abort Campaign

Abort a running campaign to stop all in-progress message deliveries.

Activate a triggered campaign

Activates a triggered campaign by its unique ID, allowing it to process events and send messages.

Archive Campaigns

Archives one or more campaigns.

Bulk Update Users

Bulk update user data in Iterable.

Cancel Campaign

Cancel a scheduled or recurring campaign in Iterable.

Cancel Email

Cancel a scheduled email to a specific user in Iterable.

Cancel Export

Cancel a queued or running export created with the 'Start export' endpoint.

Cancel In-App Message

Cancel a scheduled in-app message to a specific user in Iterable.

Cancel Push

Cancel a scheduled push notification to a specific user in Iterable.

Cancel Web Push

Cancel a scheduled web push notification to a specific user in Iterable.

Cancel WhatsApp

Cancel a scheduled WhatsApp message to a specific user in Iterable.

Create a new campaign

Creates a new blast or triggered campaign from an existing template.

Create a catalog

Create a catalog with the specified name in Iterable.

Create Catalog Items

Asynchronously creates or updates up to 1000 catalog items with a single request.

Create a new list

Create a new static list in Iterable.

Create snippet

Creates a new code snippet in Iterable.

Deactivate Triggered Campaign

Deactivate a triggered campaign in Iterable.

Bulk delete templates

Bulk delete one or more base templates from Iterable.

Delete a catalog

Delete a catalog by its name.

Delete a Catalog Item

Deletes the specified item from a catalog.

Delete Catalog Items

Asynchronously deletes catalog items from a specified catalog in Iterable.

Delete a list

Delete a list by its listId.

Delete Metadata Table

Asynchronously deletes a metadata table by its table name.

Delete snippet

Deletes a snippet by its ID (numeric) or name (string).

Delete User By ID

Asynchronously deletes a user by userId from Iterable.

Export data to CSV

Export campaign analytics data in CSV format from Iterable.

Export Campaign Data to JSON

Export campaign analytics data in JSON format with one entry per line.

Export User Events

Export all events for a user identified by email or userId.

Forget User

Deletes the specified user's data from the Iterable project and prevents future data collection about them.

Get campaign by ID

Retrieves a campaign by its unique ID.

Get Campaign Metrics

Retrieve performance metrics for one or more campaigns.

Get Catalog Field Mappings

Tool to retrieve field mappings (field to data type) and undefined fields for a catalog in Iterable.

Get catalog item by ID

Retrieves a specific catalog item by its ID from the specified catalog.

Get email template by ID

Get an email template by templateId.

Get Embedded Messages

Retrieves embedded messages for which the specified user is eligible, grouped by placementId.

Get Embedded Template

Retrieves an embedded message template by its unique ID.

Get Experiment Metrics

Retrieve metrics for email experiments.

Get In-App Messages

Get a user's in-app messages from Iterable.

Get in-app template by ID

Retrieves an in-app template by its unique ID.

Get List Size

Get the number of users within a list.

Get push template by ID

Retrieves a push template by its unique ID.

Get SMS template

Retrieves an SMS template by its unique ID.

Get snippet by ID or name

Retrieves a snippet by its ID (numeric) or name (string).

Get template by client template ID

Retrieves an email template by its client-defined template ID.

Get User By ID

Get a user by userId from Iterable.

Get User By ID (Path)

Get a user by userId (path parameter) from Iterable.

Get User Events

Get events for a specific user by userId.

Get User Sent Messages

Get messages sent to a user by email address or userId.

Get Web In-App Messages

Get a user's web in-app messages from Iterable.

List all campaigns

Retrieves metadata about all campaigns in a project with optional pagination.

List Catalog Items

Get the catalog items for a catalog.

List Catalogs

Tool to retrieve all catalog names from Iterable.

List Channels

Get all message channels within the Iterable project.

List export files

Get the job status and files for an export started with the 'Start export' endpoint.

List Export Jobs

Retrieve a list of recent export jobs for the current project.

List Forgotten User IDs

Get hashed user IDs of forgotten users for GDPR compliance.

List Journeys

Get a list of journeys (workflows) within your Iterable project.

List Lists

Retrieve all lists within a project.

List List Users

Get all users within a list.

List Message Types

Lists all message types within a project.

List Metadata Keys

List all keys in a metadata table.

List Metadata Tables

List available metadata tables in Iterable.

List recurring campaign child campaigns

Retrieve the child campaigns generated by a recurring campaign.

List Snippets

Get all snippets for the current project.

List all templates

Retrieves metadata about all templates in a project with optional pagination.

List User Fields

Get all user fields within a project.

List Webhooks

Get all webhooks configured within the Iterable project.

Merge Users

Merge two user profiles in Iterable.

Preview email template

Generate a fully rendered HTML preview of an email template using custom data.

Preview in-app template

Generate a fully rendered HTML preview of an in-app template using custom data.

Preview List Users

Get a random sample of up to 5000 users within a list.

Replace Catalog Item

Asynchronously creates or replaces the specified catalog item in the given catalog.

Replace Metadata Item

Asynchronously creates or replaces the metadata item associated with the specified key.

Schedule Campaign

Schedule an existing campaign to be sent at a specified time.

Send Campaign

Send an existing campaign immediately in Iterable.

Send email template proof

Send a proof of an email template to a specific user.

Send in-app notification to target

Send an in-app notification to a specific user using Iterable.

Send in-app template proof

Send a proof of an in-app template to a specific user using Iterable.

Send push to target

Send a push notification to a specific user using Iterable.

Send push template proof

Send a proof of a push template to a specific user.

Send SMS template proof

Send a proof of an SMS template to a specific user.

Send WhatsApp to target

Send a WhatsApp message to a specific user using Iterable.

Start Export

Start a data export job.

Subscribe to List

Subscribe one or more users to a specific list in Iterable.

Subscribe User By ID

Subscribes a user to the specified subscription group by their userId.

Track Embedded Click

Tracks a click event on an embedded message.

Track Embedded Received

Track that an embedded message was received on a device.

Track Embedded Session

Tracks an embedded message session and related impressions in Iterable.

Track Event

Track an event in Iterable.

Track Events in Bulk

Track multiple events in bulk in Iterable.

Track Purchase

Track a purchase event in Iterable.

Trigger Campaign

Trigger a campaign to send to one or more lists of recipients.

Trigger Journey

Trigger a journey (workflow) in Iterable for a specific user or list.

Unforget User

Unforgets a previously forgotten user in Iterable, resuming data collection.

Unsubscribe from list

Remove users from a list.

Unsubscribe User By ID

Unsubscribes a user from the specified subscription group by their userId.

Update Shopping Cart

Update a user's shopping cart items in Iterable.

Update Catalog Field Mappings

Set a catalog's field mappings (data types) in Iterable.

Update Catalog Item

Asynchronously creates or updates the specified catalog item in the given catalog.

Update email template

Update an existing email template in Iterable.

Update Embedded Template

Updates an embedded message template with the specified fields.

Update in-app template

Update an existing in-app template in Iterable.

Update push template

Updates an existing push template in Iterable.

Update SMS template

Update an existing SMS template in Iterable.

Update snippet by ID or name

Updates an existing snippet by ID (numeric) or creates/updates a snippet by name (string).

Update User

Update user data or add a user if none exists in Iterable.

Update User Email

Updates a user's email address in Iterable.

Update User Subscriptions

Updates user subscription preferences in Iterable.

Bulk Update User Subscriptions

Bulk update subscription preferences for multiple users in Iterable.

Update Webhook

Update an existing webhook configuration in Iterable.

Upsert email template

Create or update an email template in Iterable.

Upsert Embedded Template

Creates an embedded message template if it doesn't exist, or updates all embedded message templates that match the provided clientTemplateId.

Upsert in-app template

Create or update an in-app template in Iterable.

Upsert push template

Create or update a push template in Iterable.

Upsert SMS template

Create or update an SMS template in Iterable.

Verify SMS Code

Verifies an SMS verification code sent to a phone number in Iterable.

FRAMEWORKS

How to build Iterable MCP Agent with another framework

OpenAI Agents SDK

Use Iterable MCP with OpenAI Agents SDK

Claude Agent SDK

Use Iterable MCP with Claude Agent SDK

Claude Code

Use Iterable MCP with Claude Code

Claude Cowork

Use Iterable MCP with Claude Cowork

Codex

Use Iterable MCP with Codex

OpenClaw

Use Iterable MCP with OpenClaw

Hermes

Use Iterable MCP with Hermes

CLI

Use Iterable MCP with CLI

Google ADK

Use Iterable MCP with Google ADK

LangChain

Use Iterable MCP with LangChain

Mastra AI

Use Iterable MCP with Mastra AI

LlamaIndex

Use Iterable MCP with LlamaIndex

CrewAI

Use Iterable MCP with CrewAI

MORE TOOLKITS

Explore Other Toolkits

Toolkit marketplace

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Oauth2

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.

AimTell

Api Key

AimTell is a web push notification platform for managing websites, subscribers, campaigns, segments, and delivery analytics. Use it to send targeted browser notifications and measure engagement across your web push campaigns.

Bigmailer

Api Key

BigMailer is an email marketing platform for managing multiple brands with white-labeling and automation. It helps teams streamline campaigns and simplify integration with Amazon SES.

Brandfetch

Api Key

Brandfetch is an API that delivers company logos, colors, and visual branding assets. It helps marketers and developers keep brand visuals consistent everywhere.

FAQ

Frequently asked questions

With a standalone Iterable MCP server, the agents and LLMs can only access a fixed set of Iterable tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Iterable and many other apps based on the task at hand, all through a single MCP endpoint.

Yes, you can. Vercel AI SDK v6 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 Iterable tools.

Yes, absolutely. You can configure which Iterable 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.

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 Iterable data and credentials are handled as safely as possible.

Start with Iterable.It takes 30 seconds.

Managed auth, hosted MCP servers, and every Iterable tool your agent needs.Free to start.

Start building

Customer stories

Teams ship real agents on Composio

GET STARTED FOR FREE BOOK A DEMO

Karan skipped his own birthday party to fix our critical issue. It was 10pm and he diverted his Waymo to help us instead. This really sets the bar — it shows the commitment you need when users rely on your software.

Harsha Gaddipati

Co-founder, Slashy

A lot of students tell us that the moment their connected tools start talking to each other inside Opennote feels almost magical. The agent just knows them, and it's immensely helped keep new users on the platform.

Abhi Arya

Co-founder, Opennote

We chose Composio over Pipedream because it delivered depth where it mattered — niche tools and tricky edge cases other platforms simply ignored. That gave us confidence to scale without compromising.

Nirman Dave

CEO, Zams

As a solo builder, shipping fast is life or death. The only way I can outcompete incumbents is by outmanoeuvring them. Getting bogged down managing agent auth would have been a death sentence.

Ryan Yu

Founder, Extra Thursday

Before Composio, adding tool integrations was slow and resource-intensive. Each one could take weeks of engineering time, and maintaining them meant constantly keeping up with API changes.

Tomisin Jenrola

Founder & CEO, SwarmZero

With hands-on help from their founder, we integrated Gmail and Google Drive in just 30 minutes. This level of personal support and commitment is exactly what startups should strive for.

Jerome Leclanche

Co-Founder, Ingram Technologies

How to integrate Iterable MCP with Vercel AI SDK v6

Connect Iterable without auth hassles

Introduction

Also integrate Iterable with

TL;DR

What is Vercel AI SDK?

What is the Iterable MCP server, and what's possible with it?

What is the Composio tool router, and how does it fit here?

What is Composio SDK?

How the Composio SDK works

Step-by-step Guide

Prerequisites

Getting API Keys for OpenAI and Composio

Install required dependencies

Set up environment variables

Import required modules and validate environment

Create Tool Router session and initialize MCP client

Connect to MCP server and retrieve tools

Initialize conversation and CLI interface

Handle user input and stream responses with real-time tool feedback

Complete Code

Conclusion

Supported Tools

How to build Iterable MCP Agent with another framework

OpenAI Agents SDK

Claude Agent SDK

Claude Code

Claude Cowork

Codex

OpenClaw

Hermes

CLI

Google ADK

LangChain

Mastra AI

LlamaIndex

CrewAI

Explore Other Toolkits

Facebook

AimTell

Bigmailer

Brandfetch

Frequently asked questions

What are the differences in Tool Router MCP and Iterable MCP?+

Can I use Tool Router MCP with Vercel AI SDK v6?+

Can I manage the permissions and scopes for Iterable while using Tool Router?+

How safe is my data with Composio Tool Router?+

Start with Iterable.It takes 30 seconds.

Teams ship real agents on Composio