How to integrate Lettr MCP with Mastra AI

This guide walks you through connecting Lettr to Mastra AI 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 Mastra AI 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.

60 Tools

Introduction

This guide walks you through connecting Lettr to Mastra AI 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 Mastra AI 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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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 Lettr tools
  • Connect Mastra's MCP client to the Composio generated MCP URL
  • Fetch Lettr 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 Lettr 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 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 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
2

Getting API Keys for OpenAI and Composio

OpenAI API Key
  • Go to the OpenAI dashboard 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.
  • Go to Settings and copy your API key.
  • This key lets your Mastra agent talk to Composio and reach Lettr through MCP.
3

Install dependencies

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

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
4

Set up environment variables

bash
COMPOSIO_API_KEY=your_composio_api_key_here
COMPOSIO_USER_ID=your_user_id_here
OPENAI_API_KEY=your_openai_api_key_here

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
5

Import libraries and validate environment

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,
});
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
6

Create a Tool Router session for Lettr

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

  const composioMCPUrl = session.mcp.url;
  console.log("Lettr MCP URL:", composioMCPUrl);
What's happening:
  • create spins up a short-lived MCP HTTP endpoint for this user
  • The toolkits array contains "lettr" for Lettr access
  • session.mcp.url is the MCP URL that Mastra's MCPClient will connect to
7

Configure Mastra MCP client and fetch tools

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);
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 Lettr toolkit
8

Create the Mastra agent

typescript
const agent = new Agent({
    name: "lettr-mastra-agent",
    instructions: "You are an AI agent with Lettr tools via Composio.",
    model: "openai/gpt-5",
  });
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
9

Set up interactive chat interface

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: {
        lettr: 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);
});
What's happening:
  • messages keeps the full conversation history in Mastra's expected format
  • agent.generate runs the agent with conversation history and Lettr 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

Complete Code

Here's the complete code to get you started with Lettr and Mastra AI:

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: ["lettr"],
  });

  const composioMCPUrl = session.mcp.url;

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

  const composioTools = await mcpClient.getTools();

  const agent = new Agent({
    name: "lettr-mastra-agent",
    instructions: "You are an AI agent with Lettr 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: { lettr: 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 Lettr 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
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.

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. 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 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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