How to integrate Lettr MCP with Pydantic AI

This guide walks you through connecting Lettr to Pydantic 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 Pydantic 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.

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Introduction

This guide walks you through connecting Lettr to Pydantic 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 Pydantic 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.

Also integrate Lettr with

OpenAI Agents SDKClaude Agent SDKClaude CodeClaude CoworkCodexOpenClawHermesCLIGoogle ADKLangChainVercel AI SDKMastra AILlamaIndexCrewAI

TL;DR

Here's what you'll learn:
  • How to set up your Composio API key and User ID
  • How to create a Composio Tool Router session for Lettr
  • How to attach an MCP Server to a Pydantic AI agent
  • How to stream responses and maintain chat history
  • How to build a simple REPL-style chat interface to test your Lettr workflows

What is Pydantic AI?

Pydantic AI is a Python framework for building AI agents with strong typing and validation. It leverages Pydantic's data validation capabilities to create robust, type-safe AI applications.

Key features include:

  • Type Safety: Built on Pydantic for automatic data validation
  • MCP Support: Native support for Model Context Protocol servers
  • Streaming: Built-in support for streaming responses
  • Async First: Designed for async/await patterns

What is the 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:
  • Python 3.9 or higher
  • A Composio account with an active API key
  • Basic familiarity with Python and async programming
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 dependencies

bash
pip install composio pydantic-ai python-dotenv

Install the required libraries.

What's happening:

  • composio connects your agent to external SaaS tools like Lettr
  • pydantic-ai lets you create structured AI agents with tool support
  • python-dotenv loads your environment variables securely from a .env file
4

Set up environment variables

bash
COMPOSIO_API_KEY=your_composio_api_key_here
USER_ID=your_user_id_here
OPENAI_API_KEY=your_openai_api_key

Create a .env file in your project root.

What's happening:

  • COMPOSIO_API_KEY authenticates your agent to Composio's API
  • USER_ID associates your session with your account for secure tool access
  • OPENAI_API_KEY to access OpenAI LLMs
5

Import dependencies

python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerStreamableHTTP

load_dotenv()
What's happening:
  • We load environment variables and import required modules
  • Composio manages connections to Lettr
  • MCPServerStreamableHTTP connects to the Lettr MCP server endpoint
  • Agent from Pydantic AI lets you define and run the AI assistant
6

Create a Tool Router Session

python
async def main():
    api_key = os.getenv("COMPOSIO_API_KEY")
    user_id = os.getenv("USER_ID")
    if not api_key or not user_id:
        raise RuntimeError("Set COMPOSIO_API_KEY and USER_ID in your environment")

    # Create a Composio Tool Router session for Lettr
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["lettr"],
    )
    url = session.mcp.url
    if not url:
        raise ValueError("Composio session did not return an 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 session.mcp.url is the MCP server URL that your agent will use
7

Initialize the Pydantic AI Agent

python
# Attach the MCP server to a Pydantic AI Agent
lettr_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
agent = Agent(
    "openai:gpt-5",
    toolsets=[lettr_mcp],
    instructions=(
        "You are a Lettr assistant. Use Lettr tools to help users "
        "with their requests. Ask clarifying questions when needed."
    ),
)
What's happening:
  • The MCP client connects to the Lettr endpoint
  • The agent uses GPT-5 to interpret user commands and perform Lettr operations
  • The instructions field defines the agent's role and behavior
8

Build the chat interface

python
# Simple REPL with message history
history = []
print("Chat started! Type 'exit' or 'quit' to end.\n")
print("Try asking the agent to help you with Lettr.\n")

while True:
    user_input = input("You: ").strip()
    if user_input.lower() in {"exit", "quit", "bye"}:
        print("\nGoodbye!")
        break
    if not user_input:
        continue

    print("\nAgent is thinking...\n", flush=True)

    async with agent.run_stream(user_input, message_history=history) as stream_result:
        collected_text = ""
        async for chunk in stream_result.stream_output():
            text_piece = None
            if isinstance(chunk, str):
                text_piece = chunk
            elif hasattr(chunk, "delta") and isinstance(chunk.delta, str):
                text_piece = chunk.delta
            elif hasattr(chunk, "text"):
                text_piece = chunk.text
            if text_piece:
                collected_text += text_piece
        result = stream_result

    print(f"Agent: {collected_text}\n")
    history = result.all_messages()
What's happening:
  • The agent reads input from the terminal and streams its response
  • Lettr API calls happen automatically under the hood
  • The model keeps conversation history to maintain context across turns
9

Run the application

python
if __name__ == "__main__":
    asyncio.run(main())
What's happening:
  • The asyncio loop launches the agent and keeps it running until you exit

Complete Code

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

python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerStreamableHTTP

load_dotenv()

async def main():
    api_key = os.getenv("COMPOSIO_API_KEY")
    user_id = os.getenv("USER_ID")
    if not api_key or not user_id:
        raise RuntimeError("Set COMPOSIO_API_KEY and USER_ID in your environment")

    # Create a Composio Tool Router session for Lettr
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["lettr"],
    )
    url = session.mcp.url
    if not url:
        raise ValueError("Composio session did not return an MCP URL")

    # Attach the MCP server to a Pydantic AI Agent
    lettr_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
    agent = Agent(
        "openai:gpt-5",
        toolsets=[lettr_mcp],
        instructions=(
            "You are a Lettr assistant. Use Lettr tools to help users "
            "with their requests. Ask clarifying questions when needed."
        ),
    )

    # Simple REPL with message history
    history = []
    print("Chat started! Type 'exit' or 'quit' to end.\n")
    print("Try asking the agent to help you with Lettr.\n")

    while True:
        user_input = input("You: ").strip()
        if user_input.lower() in {"exit", "quit", "bye"}:
            print("\nGoodbye!")
            break
        if not user_input:
            continue

        print("\nAgent is thinking...\n", flush=True)

        async with agent.run_stream(user_input, message_history=history) as stream_result:
            collected_text = ""
            async for chunk in stream_result.stream_output():
                text_piece = None
                if isinstance(chunk, str):
                    text_piece = chunk
                elif hasattr(chunk, "delta") and isinstance(chunk.delta, str):
                    text_piece = chunk.delta
                elif hasattr(chunk, "text"):
                    text_piece = chunk.text
                if text_piece:
                    collected_text += text_piece
            result = stream_result

        print(f"Agent: {collected_text}\n")
        history = result.all_messages()

if __name__ == "__main__":
    asyncio.run(main())

Conclusion

You've built a Pydantic AI agent that can interact with Lettr through Composio's Tool Router. With this setup, your agent can perform real Lettr actions through natural language. You can extend this further by:
  • Adding other toolkits like Gmail, HubSpot, or Salesforce
  • Building a web-based chat interface around this agent
  • Using multiple MCP endpoints to enable cross-app workflows (for example, Gmail + Lettr for workflow automation)
This architecture makes your AI agent "agent-native", able to securely use APIs in a unified, composable way without custom integrations.
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

Vercel AI SDK logo

Vercel AI SDK

Use Lettr MCP with Vercel AI SDK

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. Pydantic AI fully supports MCP integration. You get structured tool calling, message history handling, and model orchestration while Tool Router takes care of discovering and serving the right 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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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.

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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.

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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.

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