How to integrate Lettr MCP with Vercel AI SDK v6

This guide walks you through connecting Lettr to Vercel AI SDK v6 using the Composio tool router. By the end, you'll have a working Lettr agent that can create email templates, add your contacts, create audience segments, create your lists, and set up webhooks through natural language commands. This guide will help you understand how to give your Vercel AI SDK agent real control over a Lettr account through Composio's Lettr MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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Lettr is an email and messaging platform for transactional delivery, templates, audiences, campaigns, domains, and webhooks. Use it to send reliable product emails and manage customer messaging from one place.

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Introduction

This guide walks you through connecting Lettr to Vercel AI SDK v6 using the Composio tool router. By the end, you'll have a working Lettr agent that can create email templates, add your contacts, create audience segments, create your lists, and set up webhooks through natural language commands.

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

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

Also integrate Lettr with

OpenAI Agents SDKClaude Agent SDKClaude CodeClaude CoworkCodexOpenClawHermesCLIGoogle ADKLangChainMastra AILlamaIndexCrewAI

TL;DR

Here's what you'll learn:
  • How to set up and configure a Vercel AI SDK agent with Lettr integration
  • Using Composio's Tool Router to dynamically load and access Lettr 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 Lettr MCP server, and what's possible with it?

The Lettr MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Lettr account. It provides structured and secure access to your audiences, templates, campaigns, sending domains, webhooks, and email delivery records, so your agent can organize contacts, create templates, configure sending resources, monitor campaigns, and track emails on your behalf.

  • Audience and contact management: Have your agent create, find, and delete contacts, organize them into lists, and manage their list memberships.
  • Segments, properties, and topics: Let the agent define contact properties, build dynamic audience segments, and manage public or private subscription topics.
  • Email template management: Direct your agent to create and publish HTML or editor-based templates, inspect required merge tags, retrieve template content, or remove old templates.
  • Campaign and delivery monitoring: Instruct your agent to review campaigns, delivery and engagement statistics, campaign events, sent email status, and scheduled email activity, or cancel an email before processing begins.
  • Domains and webhook configuration: Have your agent register sending domains, check DNS and verification status, and create or remove event webhooks with supported authentication settings.

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:

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

Step-by-step Guide

Step by step09 STEPS
1

Prerequisites

Before you begin, make sure you have:
  • Node.js and npm installed
  • A Composio account with API key
  • An OpenAI API key
2

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.
3

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
4

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
5

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
6

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: ["lettr"],
  });

  const mcpUrl = session.mcp.url;
What's happening:
  • We're creating a Tool Router session that gives your agent access to Lettr 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 Lettr-related tools through the MCP protocol
7

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 Lettr tools that the agent can use
8

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 lettr, 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
9

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 Lettr 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 Lettr 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: ["lettr"],
  });

  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 lettr, 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 Lettr 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 Lettr action and event your agent gets out of the box.

Attach Contacts to Lists

Attach every combination of 1-1000 contacts and 1-50 audience lists, processing up to 50,000 contact-list pairs and reporting new and existing memberships.

Bulk Create Audience Contacts

Create or recognize up to 1000 normalized, deduplicated contacts.

Cancel Scheduled Email

Cancel a scheduled email before its delivery time; cancellation is unavailable once processing has begun.

Create Audience Contact

Create one audience contact with optional properties and list membership.

Create Audience Contact With Double Opt-In

Create an unverified audience contact and irreversibly send an external confirmation email; the contact becomes subscribed only after confirming.

Create Audience List

Create a uniquely named audience list for grouping contacts.

Create Audience Property

Define a custom contact property with an immutable name and value type.

Create Audience Segment

Create a dynamic audience segment whose condition groups are ANDed while conditions inside each group are ORed.

Create Audience Topic

Create a public or private subscription topic with an immutable opt-in or opt-out default.

Create Domain

Register a sending domain and return the DNS configuration needed to verify it.

Create Template

Create and publish an email template from either custom HTML or Topol editor JSON, extracting its merge tags.

Create Webhook

Create an active event webhook using no authentication, HTTP Basic credentials, or OAuth 2 client credentials.

Delete Audience Contact

Permanently delete one audience contact and its associated memberships.

Delete Audience Lists

Permanently delete between 1 and 50 audience lists in one request.

Delete Audience Property

Permanently delete a custom contact-property definition.

Delete Audience Segment

Permanently delete one dynamic audience segment.

Delete Audience Topic

Permanently delete one audience subscription topic.

Delete Domain

Permanently remove a sending domain from Lettr and SparkPost so it can no longer send email.

Delete Template

Permanently delete an email template and all of its versions.

Delete Webhook

Permanently remove a webhook so Lettr stops delivering events to it.

Detach Contacts from Lists

Detach every combination of 1-1000 contacts and 1-50 audience lists, reporting removed and absent memberships.

Get Audience Contact

Retrieve one contact's email, status, custom properties, list memberships, and topic subscriptions by ID.

Get Audience List

Retrieve one audience list and its current contact count by ID.

Get Audience Property

Retrieve one custom contact-property definition and its fallback value.

Get Audience Segment

Retrieve one dynamic segment's list restriction, complete AND-of-OR condition definition, and cached contact count.

Get Audience Topic

Retrieve one subscription topic's defaults, visibility, and current contact count.

Get Campaign

Retrieve one campaign's name, subject, sender and reply-to configuration, schedule, rendered HTML, lifecycle state, recipient counts, and engagement statistics.

Get Domain

Retrieve one sending domain's send readiness, DNS records, provider detection, and verification status.

Get Email

Retrieve a sent email's delivery state, recipients, schedule metadata, and events by request ID.

Get Scheduled Email

Retrieve a scheduled email's current state and events by transmission ID, including after it has been processed.

Get Template

Retrieve an email template's metadata, active HTML or editor JSON content, and version counts by slug.

Get Template Merge Tags

Return required and optional merge tags for a template's active or specified version before sending with substitution data.

Get Webhook

Retrieve one webhook's target, enabled state, event selection, authentication mode, and latest delivery status.

List Audience Contacts

Return one cursor-controlled page of contacts, optionally filtered by search text, status, list, or segment.

List Audience Lists

Return one cursor-controlled page of audience lists with each list's contact count.

List Audience Properties

Return one cursor-controlled page of custom contact-property definitions and fallback values.

List Audience Segments

Return one cursor-controlled page of dynamic audience segments, including their complete AND-of-OR condition definitions, optionally filtered by list.

List Audience Topics

Return one cursor-controlled page of subscription topics with defaults, visibility, and contact counts.

List Campaign Events

Return one cursor-controlled page of a campaign's delivery and engagement events, with event, recipient, and time filters.

List Campaigns

Return one cursor-controlled page of campaigns with complete delivery and engagement statistics, optionally filtered by lifecycle status.

List Domains

Return all sending domains with approval, DNS verification, and send-readiness status.

List Email Events

Return one cursor-controlled page of delivery and engagement events across sent emails, with event, recipient, transmission, bounce, and date filters.

List Sent Emails

Return one cursor-controlled page of sent emails, optionally filtered by recipient and date range.

List Projects

Return one cursor-controlled page of Lettr projects and their IDs for use with template operations.

List Templates

Return one cursor-controlled page of email templates for a project or the team's default project.

List Webhooks

Return all event webhooks with target, enabled state, event selection, authentication mode, and latest delivery status.

Publish Template Version

Create and activate a new version of an existing email template from exactly one of HTML or Topol editor JSON, optionally renaming the template atomically.

Schedule Campaign

Schedule a campaign for future delivery or reschedule it.

Schedule Email

Create a transactional email scheduled 5 minutes to 3 days in the future; it remains cancellable until processed.

Send Campaign

Immediately and irreversibly start sending a sendable draft campaign to its resolved audience.

Send Email

Immediately queue a transactional email to up to 50 recipients using inline content or a Lettr template.

Unschedule Campaign

Cancel a scheduled campaign send and return the campaign to draft.

Update Audience Contact

Change a contact's email, subscribed or unsubscribed status, or selected custom property values.

Update Audience List

Rename an audience list while preserving its contacts.

Update Audience Property

Set or clear a custom contact property's fallback value.

Update Audience Segment

Change a dynamic segment's name, optional audience-list restriction, or complete AND-of-OR condition definition.

Update Audience Topic

Change a subscription topic's name, description, or public/private visibility.

Update Template

Rename an email template's metadata without publishing a new version.

Update Webhook

Partially update a webhook's name, callback URL, authentication, selected events, or active state.

Verify Domain

Run Lettr's DNS verification for a registered domain and return DKIM, CNAME, DMARC, SPF, and ownership results.

FRAMEWORKS

How to build Lettr MCP Agent with another framework

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Lettr MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Lettr MCP with Claude Agent SDK

Claude Code logo

Claude Code

Use Lettr MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Lettr MCP with Claude Cowork

Codex logo

Codex

Use Lettr MCP with Codex

OpenClaw logo

OpenClaw

Use Lettr MCP with OpenClaw

Hermes logo

Hermes

Use Lettr MCP with Hermes

CLI logo

CLI

Use Lettr MCP with CLI

Google ADK logo

Google ADK

Use Lettr MCP with Google ADK

LangChain logo

LangChain

Use Lettr MCP with LangChain

Mastra AI logo

Mastra AI

Use Lettr MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Lettr MCP with LlamaIndex

CrewAI logo

CrewAI

Use Lettr MCP with CrewAI

FAQ

Frequently asked questions

With a standalone Lettr MCP server, the agents and LLMs can only access a fixed set of Lettr tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Lettr 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 Lettr tools.

Yes, absolutely. You can configure which Lettr 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 Lettr data and credentials are handled as safely as possible.

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