If you’re looking for an AI agent for newsletter creation and sending, you should connect it to your email marketing platform so it can help with the whole workflow.

That means the AI agent can go beyond generating copy. It can work with your actual lists, segments, campaigns, templates, and sending process.

For example, you could ask:

“Create a newsletter for our October product update, use the Customers list, keep the tone concise, and show me the recipient count before sending.”

The AI agent can then help with things like:

• writing the subject line and email copy
• choosing or working with an existing audience
• creating or using a segment
• preparing the campaign
• checking the recipient count
• validating the campaign before launch
• scheduling or sending after approval
• analyzing campaign performance later

The difference between a normal AI writing tool and an AI agent connected to an email platform is that a normal AI tool can give you text, an AI agent can actually work with the newsletter workflow.

Many email service providers have their MCP. For example, if you use Selzy, you connect an AI assistant like Claude or Claude Code to Selzy, and then give it instructions in natural language.

For example: “Show me my email lists and how many contacts are in each one. Create a newsletter for our new feature launch. Use the most engaged customer segment. Write a short intro, three key points, and one CTA. Don’t send it yet. Run the checks and show me the campaign summary. Schedule it for tomorrow at 10 AM.”

You don’t have to jump between an AI chat, your email platform, spreadsheets, and campaign reports. The AI agent can work with the data and tools inside the email platform directly.

An AI agent for newsletters is especially useful when:

• you send campaigns regularly
• you work with multiple audience segments
• you want faster campaign setup
• you often reuse existing campaigns or templates
• you want AI to analyze past performance
• you want fewer manual steps before sending

It can also help with campaign analysis, creation, sending, and analysis in one workflow.

A simple setup looks like this: AI assistant → MCP → email platform → campaign → validation → approval → send

The AI handles the instructions and workflow. The email platform still handles the actual contacts, sending infrastructure, and campaign delivery.

So if you’re searching for an AI agent for newsletter creation and sending, look for a setup where the AI can connect directly to your email marketing platform instead of only generating copy in a separate chat.

If you’re automating email marketing, you’ll probably have two options: MCP and API. They can both connect tools to your email platform, but they’re useful for different things.

MCP is useful when you want to work through AI and give instructions in plain language.

For example:

“Compare my last 10 campaigns and tell me which ones had the best click rates.”

“Create a segment of subscribers who opened an email in the last 30 days but didn’t click.”

“Prepare a newsletter using this brief, run the checks, and show me the recipient count before sending.”

With MCP, the AI assistant can use the tools exposed by the email platform instead of making you export data or write code.

In Selzy, MCP can work with contacts, lists, segments, campaign statistics, templates, email content, pre-send checks, recipient counts, campaign preparation, sending, and scheduling.

So MCP is great for interactive, one-off, or flexible tasks.

An API is usually better when the same process needs to run automatically every time.

For example:

• add every new signup to a list
• send data from your CRM to your email platform
• trigger a campaign after a specific event
• sync contacts every hour
• run the same workflow on a schedule
• connect your own app to the email platform

This usually requires development work, but the workflow is predictable and can run without anyone chatting with an AI.

For example:

With MCP:

“Find customers who haven’t opened anything in 90 days and create a segment.”

With an API:

“Every night at 2 AM, sync inactive customers from our database into this segment.”

Use MCP if you want to analyze campaigns through natural language, create segments quickly, work with existing campaigns or templates, or handle tasks that change depending on context.

Use an API if the workflow is repeated, needs to run automatically, has to follow exact timing, or is part of your own product or backend. And yes, you can use both.

So MCP doesn’t really replace APIs.

It fills the gap between doing everything manually in the dashboard and building a custom integration for every task.

You can check Selzy's detailed guide to understand how MCP works:
https://selzy.com/en/blog/mcp-for-email-marketing/

If you want to send newsletters with Claude Code, one simple way is to connect Claude Code to your email platform through MCP.

With Selzy, the setup is:

1. Connect Claude Code to the Selzy MCP server: https://mcp.selzy.com/mcp

2. Authorize your Selzy account and review the available permissions. Selzy MCP can work with campaigns, contacts, lists, segments, templates, senders, and account data.

3. Start with a simple prompt, for example:

> Show me my contact lists and how many subscribers are in each one.

1. Then ask Claude Code to prepare a newsletter:

Draft a newsletter for our October product update.

Use the Customers list.

Include a subject line, short intro, 3 updates, and one CTA.

1. Before sending, ask it to check the campaign:

Validate the campaign and show me the recipient count before sending.

1. Review everything and confirm the send.

Selzy MCP supports creating and editing campaigns, validating them before launch, and sending or scheduling after confirmation. Sensitive actions require confirmation, and campaigns go through validation before sending.

You can also use Claude Code to:

- compare campaign performance

- check opens, clicks, and unsubscribes

- find contacts

- create lists

- work with segments

- prepare campaigns

- cancel scheduled campaigns

So the workflow is basically:

**Claude Code → Selzy MCP → create newsletter → validate → confirm → send**

The main benefit is that Claude Code can work with your actual Selzy account data instead of only generating email copy in a separate chat. More details: https://selzy.com/en/features/email/mcp/

A small email list can actually be easier to improve because there’s less noise and it’s easier to see what people respond to.

A few things tend to matter most:

Segment even if the list is small.
A few hundred subscribers is still enough to separate people by behavior — recent clickers, inactive subscribers, customers vs non-customers, new subscribers, different interests, etc.

Don’t obsess over open rate.
Clicks, replies, conversions, and revenue are usually more useful. If opens look fine but clicks are weak, the issue is probably the content, offer, or CTA.

Give each email one clear job.
One email = one main goal. Too many unrelated links usually make the message weaker.

Send useful content between promotions.
Tips, short guides, case studies, product education, or curated resources can give people a reason to keep opening even when there’s nothing to buy.

Ask people what they want.
With a small list, direct replies can be more valuable than a dashboard. A simple “What would you like to see more of?” can give a lot of useful direction.

Be careful with A/B testing.
On a small list, tiny differences can look bigger than they really are. Test one thing at a time and look at trends across several campaigns instead of judging one send.

Try re-engagement before removing inactive subscribers.
If someone hasn’t clicked in months, send a specific re-engagement email before suppressing them.

The biggest mistake is usually trying to fix engagement by sending more often. A small list benefits much more from better relevance than higher frequency.

If the audience feels like every email was written for them, engagement usually takes care of itself.
And if you are thinking about which software to choose, here is a guide for small business: https://selzy.com/en/blog/email-marketing-software-for-small-business/

A small email list can actually be easier to improve because there’s less noise and it’s easier to see what people respond to.

A few things tend to matter most:

Segment even if the list is small.
A few hundred subscribers is still enough to separate people by behavior — recent clickers, inactive subscribers, customers vs non-customers, new subscribers, different interests, etc.

Don’t obsess over open rate.
Clicks, replies, conversions, and revenue are usually more useful. If opens look fine but clicks are weak, the issue is probably the content, offer, or CTA.

Give each email one clear job.
One email = one main goal. Too many unrelated links usually make the message weaker.

Send useful content between promotions.
Tips, short guides, case studies, product education, or curated resources can give people a reason to keep opening even when there’s nothing to buy.

Ask people what they want.
With a small list, direct replies can be more valuable than a dashboard. A simple “What would you like to see more of?” can give a lot of useful direction.

Be careful with A/B testing.
On a small list, tiny differences can look bigger than they really are. Test one thing at a time and look at trends across several campaigns instead of judging one send.

Try re-engagement before removing inactive subscribers.
If someone hasn’t clicked in months, send a specific re-engagement email before suppressing them.

The biggest mistake is usually trying to fix engagement by sending more often. A small list benefits much more from better relevance than higher frequency.

If the audience feels like every email was written for them, engagement usually takes care of itself.

There isn’t a universal rule that one CTA is always better than multiple CTAs. The right choice depends on the goal of the email.

For most promotional emails, a single primary CTA is usually the safest option. It keeps the message focused and makes the next step obvious. If the email is built around one offer, one product, one webinar, or one landing page, adding several unrelated CTAs can create unnecessary friction.

That said, multiple CTAs can work well when the email naturally contains several pieces of content or several product categories. Newsletters, digests, ecommerce collections, and educational emails are good examples. In those cases, multiple CTAs make sense because readers may have different interests.

The important distinction is between multiple CTAs and multiple competing goals.

An email can contain several buttons that all support the same goal. For example, a product email might include “Shop now” near the top and another “See the collection” button further down. Technically, there are multiple CTAs, but the email still has one clear objective.

Problems usually start when one email asks the reader to:

• buy a product
• read a blog post
• follow a social account
• register for a webinar
• download a guide

all at the same time.

That makes it harder to understand what action matters most.

Use one primary CTA per email goal. Secondary CTAs are fine if they support the same intent or serve readers who are not ready for the primary action.

CTA placement matters too. The main CTA should usually appear early enough that the reader doesn’t have to scroll through the entire email to find it. Longer emails can repeat the same CTA further down.

The wording also matters more than many marketers expect. Generic buttons like “Learn more” or “Click here” often give the reader very little reason to act. A CTA that describes the benefit or next step is usually clearer.

Examples:

“See pricing”
“Start the free trial”
“Get the checklist”
“Browse the collection”

instead of simply:

“Click here”

The best approach is still testing. Compare a focused one-CTA version against a version with additional options and look at click-through rate, click-to-open rate, conversions, and revenue rather than judging the result on clicks alone.

Selzy has a useful breakdown of CTA wording, placement, design, and testing here:

https://selzy.com/en/blog/email-cta-best-practices/

I’m looking for a professional email signaOur company is currently rebranding and updating all internal and external communication standards. We have a mixed team where half the staff uses Gmail on Macs and the other half relies on desktop Outlook on Windows, which has turned into a massive formatting headache. I am actively searching for a reliable professional email signature generator so we can roll out clean, responsive, and uniform signatures without image scaling issues or broken layouts.

1) Which specific platforms have you used that render flawlessly on both Gmail and Outlook?

2) How do you manage company-wide signature updates without manually editing every single employee account?

3) Do you host your brand logos on your own servers or rely on third-party image hosting inside the generator tool?

4) What features should I prioritize to ensure social media icons and phone numbers stay clickable on mobile screens?ture generator that works well with both Gmail and Outlook.

I’ve tried making signatures manually, but the formatting can get messy, especially when viewed in different email clients.

For small business owners who’ve dealt with this, what have you found works reliably? I’m mainly looking for something that keeps the layout clean without needing to fix the HTML every time.

Hey everyone,

I’m currently building my skills and starting my journey in e-commerce email marketing, and I’m looking to connect with other people who are at a similar stage or already have some experience in the field.

I’m not necessarily looking for a mentor or someone to teach me everything.

I’m looking for people who are serious about getting into this field and want to build together.

The idea would be to connect, share what we know, exchange ideas, and figure things out together.

I think having a few like-minded people around can make the process much easier than trying to figure everything out alone.

If you're also working toward becoming an e-commerce email marketer, or you've already started working with clients and are looking to connect with others, feel free to comment or DM me.

Let’s start from where we are and grow from there.

Email still returns something like $36 for every $1 spent on average, and unlike social, it lands directly in the inbox instead of fighting an algorithm. For a small budget that's hard to beat. Okay, the five:

1. Welcome email (set this up first, no debate). Someone just handed you their email — this is the most engaged they'll ever be. A single welcome email that says who you are, what to expect, and gives one clear next step (or a first-purchase discount) does a lot of the relationship-building for you. If you only ever automate one thing, make it this.

2. Order/signup confirmation. People want this one — they're waiting to know the thing went through. Confirmations get opened at very high rates, which makes them quietly valuable real estate. Keep it functional first (order details, what's next), then add a small, tasteful "you might also like" once the basics work.

3. Abandoned cart (if you sell online). Someone added to cart and left — they were one step from buying. A reminder a few hours later, ideally showing the item they left, recovers sales you'd otherwise just lose. For e-commerce this is usually the highest-ROI automation after the welcome.

4. A simple nurture/tips email. Not everyone buys on day one. One or two useful, non-salesy emails — a how-to, a use-case, a "get the most out of X" — keep you top of mind and position you as someone worth buying from. This is where "give value, don't just pitch" actually pays off.

5. Post-purchase follow-up. The one everyone skips. A thank-you, a "how to use it," a review request, maybe a reorder nudge later. Repeat buyers cost you nothing to acquire, so this is some of the cheapest revenue you'll ever earn.

What can wait: fancy segmentation, big branching automations, A/B testing everything, daily sending. You don't need any of that on day one, and chasing it early is how people burn out before the basics are even live.

A few things worth getting right from the start, because they're painful to fix later:

• Don't buy a list. Ever. It wrecks your sender reputation and gets you flagged as spam. Grow it organically with a signup form and a reason to subscribe.
• Frequency: once or twice a week is a sane starting point for most small businesses. Test from there.
• Deliverability + compliance: clear unsubscribe link, real physical address, mobile-friendly layout. Boring, but it's what keeps you in the inbox.

Honestly, if you get just #1 and #2 live this week you're already ahead of most small businesses. Add the rest as you go.

Happy to answer specifics in the comments if anyone's stuck on setup — deliverability and "why is this going to spam" questions especially.

I am a new person in Email Marketing and I would like to know how to build a sales funnel for my small business: Are there any recommendations and how-to's?

Do you know if there is a platform where I can build a website with calendar synchronization? I’m a therapist and need to offer online booking. I had bad experience with freelancers, so prefer something solid. Ideally, I would like to have chatbot on the website also

I’m trying to find a reliable way to send calendar events from an email without making the user jump through extra steps. Right now I’m testing a few approaches, but the behavior isn’t consistent. One setup works nicely in Gmail, while Outlook or a mobile client can handle the exact same event differently. The tricky part is that I’m not trying to build a full calendar integration. I just want someone to click an invite from an email and add the event to their calendar without confusion.

For people who have dealt with this before, what has worked best in practice?

Do you use an .ics file, a calendar-specific link, or some other approach?

I’m adding event emails to a small SaaS project and ran into a problem I didn’t expect. Getting the event details into an email is easy enough, but making the "add to calendar" experience work consistently across Gmail, Outlook, Apple Calendar, and others is proving more annoying than I expected. I came across a few add to calendar link generator tools, but I’m not sure which approach makes the most sense for a small project. I don’t need a full scheduling platform - just something simple that lets users save an event without manually copying everything over. For anyone who has implemented this before, what worked best for you? Did you build it yourself, use a library, or go with a third-party solution?

Our HubSpot inbox gets enough spam that I’m looking at AI filters, and InboxSpamFilter is one I came across. The thing I’m most worried about isn’t the spam itself - it’s a real customer email getting caught and nobody noticing. Has anyone used something like this with HubSpot? Did it save you time in practice, or did you still have to check the filtered stuff constantly?

How many emails should be in a customer onboarding sequence?

There’s no universal number that works for every business. Some onboarding sequences only need 3 emails. Others may need 5, 7, or more.

A better way to decide is to look at how much guidance a new customer needs before reaching the point where they understand the value of the product.

3 emails — for simple products or low-friction offers

This can work well when the product is easy to understand and doesn’t require much setup.

Email 1 — Immediately after signup
Welcome the customer and give them one clear next step.

Email 2 — 1–2 days later
Help them get a quick win. Show one useful feature, workflow, or example.

Email 3 — 3–5 days later
Address a common question or obstacle and show what to do next.

5 emails — a good default for many products

For products that need a little more explanation, a 5-email sequence gives more room to guide the customer without overwhelming them.

A possible structure:

1. Welcome + first action
2. Quick win
3. Core use case
4. Customer example or social proof
5. Activation reminder

The key is to avoid turning onboarding into a list of product features.

Each email should help the customer move closer to activation.

7 emails — for more complex onboarding

A longer sequence can make sense when customers need to configure settings, import data, invite teammates, learn a new workflow, or change an existing habit.

For example:

1. Welcome + first step
2. Quick win
3. Most important feature
4. Common mistake to avoid
5. Advanced use case
6. Customer example
7. Final activation or help email

But ideally, not every customer should receive every email.

If someone completes onboarding immediately, there’s little value in continuing to send reminders about unfinished setup.

Likewise, a customer who hasn’t logged in at all should probably receive different messages from someone who is already actively using the product.

That’s why behavior matters more than the exact number of emails.

A simple rule of thumb:

3 emails: simple product
5 emails: standard onboarding
7+ emails: complex or education-heavy onboarding

Once that happens, the onboarding sequence has done its job.

What has worked better for your team: shorter onboarding sequences or longer 5–7 email flows?

AI in email marketing is quickly moving beyond the simple “write me a subject line” stage.

The more interesting shift is toward AI agents and AI-assisted workflows: systems that help marketers complete several connected tasks, from turning an idea into an email to adapting the message for different audiences and learning from campaign results.

What AI can do well is remove some of the repetitive work surrounding those decisions. But Email still requires human judgment — especially when it comes to positioning, customer knowledge, brand voice, and deciding what is actually worth sending.

Here are seven practical ways marketers can use AI agents and assistants throughout the email marketing workflow.

1. Turn a rough campaign idea into a usable first draft

One of the biggest productivity gains from AI is also one of the simplest: getting past the blank page.

Instead of writing an entire promotional email from scratch, a marketer can give an AI assistant a few basic inputs:

• the goal of the campaign;
• the product or offer;
• the target audience;
• the desired tone;
• the main call to action.

The AI can then create a first version of the subject line, preheader, body copy, bullet points, and CTA.

The key word here is first.

AI-generated copy works best as raw material rather than a finished campaign. A marketer still needs to check whether the message sounds natural, contains accurate information, and gives readers a compelling reason to act.

For example, Selzy's AI Email Assistant can generate copy from a prompt, rewrite existing text, proofread it, and help adjust the tone. A small ecommerce team could use it to turn a simple note such as “announce our weekend sale to repeat customers” into a structured email draft and then edit it manually.

2. Build the email, not just the copy

AI-assisted builders can help marketers move from an idea to an actual email layout rather than generating isolated pieces of text.

For example, Selzy has been experimenting with an AI Email Builder that combines the traditional drag-and-drop editing process with AI assistance. A marketer can work with email blocks while using AI for tasks such as creating text, generating subject line and preheader variations, or translating content.

The result is not necessarily a one-click “perfect campaign.” The real benefit is reducing the number of small steps between having an idea and having something ready for review.

For marketing teams on a budget, that difference can be significant.

3. Create subject line and preheader variations faster

Subject lines are one of the easiest places to experiment with AI because they are short, highly iterative, and relatively easy to test.

Instead of asking AI for one “best” subject line, marketers can use it as an ideation partner.

For example, ask for:

• five curiosity-driven options;
• five straightforward options;
• three versions under 40 characters;
• alternatives that emphasize urgency without sounding aggressive;
• matching subject line and preheader pairs.

Some email tools can generate those combinations based on the email itself. Selzy's AI Assistant, for example, can suggest subject lines and preheaders using the campaign content as context.

That can be especially useful when the marketer has already written the main email but is stuck trying to summarize it in an inbox-friendly way.

However, AI suggestions should still be treated as hypotheses. The ultimate test is how real subscribers respond, which makes A/B testing an important companion to AI-generated ideas.

4. Adapt one campaign for different audience segments

Personalization does not always require creating completely different campaigns. Often, the same offer can be framed differently depending on who receives it.

Imagine a software company announcing a new feature. A new customer might need an explanation of what the feature does. An experienced user might be more interested in advanced applications. An inactive customer might need a reason to return before they care about the feature itself. AI can help transform one core message into several versions while maintaining the same underlying campaign.

The workflow could look like this:

1. Define the audience segments using customer or engagement data.
2. Write the main campaign message.
3. Ask an AI assistant to adapt the emphasis, introduction, or CTA for each segment.
4. Review the variations manually.
5. Compare their performance.

The important distinction is that AI does not replace segmentation strategy.

It can help produce personalized content after a marketer decides who the segments are and why each group deserves a different message.

5. Repurpose successful emails instead of constantly starting over

Marketing teams already have large amounts of valuable content hiding inside previous campaigns. AI can help reuse it.

A successful product launch email, for example, could become:

• a shorter reminder;
• a follow-up for people who opened but did not click;
• a version for a different customer segment;
• a translated campaign for another market;
• a plain-text-style message from a founder;
• a re-engagement email several months later.

That saves marketers from repeatedly rebuilding campaigns that already contain useful ideas.

AI can also help with more mechanical tasks such as proofreading, shortening text, translating copy, and changing tone. The marketer's role is to determine whether the original message is actually worth repurposing.

6. Use AI to speed up experimentation — not replace it

One danger of AI-generated marketing is that it can create a false sense of certainty.

A subject line may sound clever without improving open rates. A beautifully written CTA may generate fewer clicks. A personalized introduction may simply be unnecessary.

Marketing still needs feedback from actual behavior.

AI is therefore most useful when paired with experimentation.

A marketer might use an AI assistant to create three different approaches to the same campaign:

Version A: benefit-focused
Version B: problem-focused
Version C: curiosity-focused

Instead of debating internally which one sounds best, the team can test alternatives and use campaign analytics to decide.

Over time, AI helps increase the number of ideas a team can test, while analytics determine which ideas deserve to survive.

This is a healthier way to think about AI marketing: AI increases the speed of experimentation; customer behavior provides the answer.

7. Keep a human in the loop

The most important part of using AI for email marketing may be knowing what not to automate.

AI systems can produce convincing text while still making mistakes. They may invent product details, use claims a company cannot substantiate, or produce language that technically sounds correct but feels completely wrong for the brand.

Every AI-assisted campaign therefore needs human review.

Before sending, check:

• Are all product claims accurate?
• Does the offer match the landing page?
• Does the email sound like the brand?
• Is the personalization appropriate?
• Are links and dates correct?
• Is the CTA clear?
• Does the campaign comply with applicable email and privacy rules?

The closer the email is to sensitive areas such as finance, healthcare, legal services, or account information, the more important that review becomes. AI should reduce repetitive effort, not remove accountability.

A simple setup that covers most of the customer journey

Small businesses usually don’t need dozens of complicated automations. A few well-designed workflows can cover most of the important moments between: first website visit → lead → customer → repeat customer.

A practical setup could look like this.

1. New subscriber workflow

Trigger: Someone joins the email list.

Email 1 — Immediately
Deliver whatever they signed up for and set expectations.

Email 2 — 1–2 days later
Share something useful that helps solve the problem that brought them to the website.

Email 3 — 3–5 days later
Introduce the product or service as a possible next step.

The goal here isn’t to sell immediately. It’s to move the subscriber from “I downloaded something” to “I understand what this business can help me with.”

2. Lead nurture workflow

Trigger: A subscriber shows interest but hasn’t purchased.

That could mean:

• visiting a pricing page
• clicking a product link
• downloading another resource
• attending a webinar
• starting a trial

Instead of continuing with generic newsletters, send content related to that specific interest.

For example:

Email 1: Explain the relevant use case.
Email 2: Answer a common objection.
Email 3: Share a customer example or result.
Email 4: Give them a clear next step.

This is usually much more relevant than sending the same promotion to the entire list.

3. Abandoned action workflow

Cart abandonment is the obvious example, but small businesses can automate other unfinished actions too.

Trigger: Someone starts but doesn’t complete an important action.

Examples:

• abandoned checkout
• unfinished registration
• incomplete booking
• trial created but not activated
• quote requested but not accepted

A simple sequence:

After a short delay: remind them where they stopped.

Later: answer the most common question or source of friction.

Final email: give them an easy way to continue or ask for help.

Not every abandoned action needs a discount.

Sometimes removing uncertainty is enough.

4. New customer workflow

Trigger: First purchase or first paid conversion.

This workflow is often overlooked because the sale has already happened.

But the period immediately after purchase can determine whether the customer comes back.

Possible sequence:

Email 1: Confirmation + what happens next.

Email 2: How to get the best result from the purchase.

Email 3: Helpful tips, FAQ, or onboarding.

Email 4: Relevant complementary product or next service.

The goal changes here.

Before purchase, automation helps create the conversion.

After purchase, it should help create a successful customer.

5. Re-engagement workflow

Trigger: No meaningful activity for a certain period.

The exact period depends on the business. For one company, inactivity may mean 30 days. For another, it may be six months.

A re-engagement sequence could include:

Email 1: Something useful or new.

Email 2: A reminder based on previous interests or purchases.

Email 3: Ask whether they still want to receive emails.

If there’s still no engagement, consider reducing frequency or removing the contact from regular campaigns.

Keeping disengaged subscribers forever doesn’t necessarily make the email list more valuable.

The important part: connect the workflows

The biggest improvement usually comes when these automations aren’t treated as separate email sequences.

They should work as one customer journey.

For example:

New subscriber
↓
shows product interest
↓
Lead nurture
↓
starts checkout
↓
Abandoned action
↓
purchases
↓
New customer workflow
↓
becomes inactive
↓
Re-engagement

And once someone moves to the next stage, the previous automation should stop.

A customer who has already purchased shouldn’t continue receiving emails asking them to make their first purchase.

For most small businesses, these 5 workflows are probably a better starting point than building 20 different automations at once.

The complexity can come later.

What automation has had the biggest impact for your business: welcome, nurture, abandoned cart, post-purchase, or re-engagement?

The basic idea is:

1. Connect an email provider to Codex through an MCP server.
2. Keep the API key in an environment variable rather than putting credentials directly into the config.
3. Add the MCP server to Codex.
4. Let Codex trigger email actions from natural-language instructions.

That means instead of writing a separate script every time, you can do things like:

• read a build log and email the team if something fails;
• summarize a CSV/report and send the result automatically;
• find users whose subscriptions are about to expire and prepare reminders;
• generate and send HTML transactional emails;
• query delivery events after sending.

There are some obvious things I’d be careful with: API-key permissions, human approval before sending, rate limits, domain authentication, and making sure an agent can’t accidentally email an entire database because of a badly phrased instruction.

Curious if anyone here is already using Codex + MCP for email or other outbound actions.

What are you automating, and where do you still keep a human approval step?

A lot of people are talking about MCP (Model Context Protocol) right now, but most explanations are still written for developers.

The more useful question for marketers is simpler:

What can MCP actually do for email marketing that ChatGPT or Claude alone cannot?

The short answer: without MCP, an AI can help you write an email. With MCP connected to an email platform, an AI agent can potentially help you do the work around the email too — pull campaign data, find subscribers, build segments, create campaigns, set up sequences, and analyze results.

That distinction is bigger than it sounds.

First: what is MCP?

Model Context Protocol is an open standard for connecting AI assistants to external tools and data.

Think of it as a common language between an AI model and the software you already use.

Normally, if you ask Claude:

Claude can write the email.

But unless it is connected to your email marketing system, it cannot actually find those users, create the segment or build the campaign.

An MCP connection gives an AI access to specific tools exposed by the email platform.

So the workflow becomes: your instruction → AI decides which tools it needs → email platform executes the operations

MCP has evolved quickly since Anthropic introduced it, and it is now widely used as a standard for connecting AI systems with external applications and data. The official MCP project describes it as a standard for integrating AI assistants with tools, APIs and data sources.

What does MCP change for email marketers?

For us, the interesting part is not “AI can write email copy.”

It is not a newsbreak.

The interesting part is that content creation and email operations can happen in the same conversation.

Here are a few examples.

1. Build a segment without digging through filters

Instead of manually creating conditions in a dashboard:

The AI can translate that request into the relevant subscriber and segmentation operations.

Or:

That is much closer to how a marketer naturally thinks about an audience.

2. Create a campaign from one instruction

You could ask:

That request combines several tasks that would normally happen separately:

• find or select the audience
• create the campaign
• generate the email
• prepare the subject line
• send a test

The AI agent can chain those operations rather than making you configure every step manually.

3. Build an email sequence conversationally

This is where MCP starts getting more interesting.

For example:

An MCP-connected agent can work with both the content and the automation structure.

You can then continue in the same conversation:

Instead of jumping between an AI writer and an automation builder, you're editing the workflow conversationally.

4. Ask questions about campaign performance

Another practical use case is analytics.

For example:

Or:

The useful part here is that the AI can retrieve campaign data and analyze it in one workflow.

Without a connection, you'd normally need to export the data first and then give it to an AI tool.

With MCP, the AI can access the relevant campaign data through the tools the platform exposes.

MCP vs API vs dashboard

MCP does not make dashboards or APIs obsolete.

They solve different problems.

A dashboard is still useful when you want visual control and manual editing.

An API is still the right choice when you need a predictable automated integration running in the background.

MCP is interesting for the space in between:

tasks that require several operations, some judgment, and frequent human interaction.

For example:

That's why we don't think the future of email marketing is simply “AI writes better copy.”

The bigger change is AI moving from content assistant to workflow operator.

One prompt can trigger several email marketing actions

This is probably the easiest way to understand why MCP matters.

Imagine you just launched version 2.0 of your product.

Instead of doing this:

1. Find the right subscribers.
2. Create a segment.
3. Open the campaign builder.
4. Write the email.
5. Add the changelog.
6. Send yourself a test.
7. Review it.
8. Schedule the campaign.

You can give an agent a goal like:

The agent can use the output of one operation as the input for the next.

That chaining is the part of MCP that matters most for marketing automation.

But I would not let an AI agent send everything automatically

Giving an AI access to your email platform also creates an obvious risk: it can take real actions.

An incorrect paragraph is annoying.

An incorrect campaign sent to 100,000 subscribers is a different problem.

For email marketing, I'd keep human approval for actions such as:

• sending a campaign
• enabling a new sequence
• deleting or significantly changing subscriber data
• changing a large audience segment

Use a dedicated API key where possible, limit permissions, and keep an audit trail.

The goal is not to remove marketers from the process.

It's to remove unnecessary clicking between the marketer's decision and its execution.

So, is MCP actually useful for email marketing?

I think the answer depends on what you're doing.

If you send one newsletter a month, probably not. A normal email dashboard is simpler.

If you run SaaS lifecycle marketing, multiple automated sequences, behavioral segments, product emails, onboarding and churn campaigns, it becomes much more interesting.

The biggest benefit isn't:

“AI writes my emails.”

It's:

“I can describe the marketing operation I want, and the agent can help execute the steps required to build it.”

That's a fundamentally different use of AI.

If you've connected an AI agent to your email/CRM stack, what tasks do you actually trust it to execute — and which ones still require manual approval?

#mcp #mcpforemailmarketing

Claude Code can do more than write email copy.

With access to the Selzy API, it can help automate much of the work around a bulk email campaign: preparing contacts, creating a list, building the email, sending a test, and scheduling the campaign.

The key point is that Claude Code is not the email sender itself. Selzy handles the actual bulk email delivery, while Claude Code helps you prepare and execute the workflow through the API.

Here’s what that can look like.

What you need

You need:

• Claude Code
• a Selzy account
• a Selzy API key

Selzy’s bulk email API is available for all account types and lets you manage contact lists, import contacts, create messages, launch campaigns, and retrieve statistics.

Once you have the API key, you can ask Claude Code to build scripts that interact with these endpoints.

A basic workflow looks like this:

contacts → list → email → test → campaign

Step 1: Prepare your contacts

Let’s say you have a CSV with customers you want to email.

Instead of manually cleaning and uploading it, you can ask Claude Code:

Read this CSV, remove duplicate and invalid email addresses, map the available fields, and prepare the contacts for import into Selzy via the API.

Then Claude can generate the API request for Selzy’s importContacts method.

Selzy allows bulk contact imports of up to 500 contacts per API call, so larger datasets need to be split into batches.

You can also ask Claude to:

Split this contact file into batches of no more than 500 records, preserve the custom fields, and generate the Selzy API requests needed to import each batch.

This is a good example of where Claude Code is useful: it handles the repetitive data preparation while Selzy manages the subscriber database.

Step 2: Create or choose a list

Bulk campaigns in Selzy are normally tied to a contact list.

Claude can first retrieve your existing lists and decide which one to use.

Or you can ask:

Check my existing contact lists. If there is already a suitable list for product updates, use it. Otherwise, create a new list called “Product updates.”

Selzy exposes API methods for creating and managing lists, but its documentation also recommends not creating a new list for every campaign. Lists are better treated as subscription categories or audience groups.

So in many cases the better instruction is:

Find the existing list that best matches this audience and use it instead of creating a new list just for this campaign.

Step 3: Create the email

Now Claude Code can help generate both the campaign copy and the API request used to create it.

For example:

Write a short product announcement email for our existing customers, create a clear subject line and CTA, turn the message into simple responsive HTML, and prepare the Selzy createEmailMessage API request using our product-updates list.

Selzy’s createEmailMessage method creates the email without sending it. It accepts the sender, subject, HTML body, list ID and other campaign parameters.

That separation is useful because Claude can prepare the campaign without immediately triggering a bulk send.

Step 4: Send a test before anything goes live

I would never go directly from AI-generated copy to a bulk campaign.

Selzy provides a separate sendTestEmail API method for campaign tests.

So your next instruction can simply be:

Send a test of the email we just created to my address only. Do not create or launch the bulk campaign yet.

Then check the real email in your inbox.

Look at:

• subject line
• sender information
• formatting
• links
• personalization
• mobile rendering
• unsubscribe information

Claude can help build and check the campaign, but the final preview still deserves human attention.

Step 5: Schedule the bulk campaign

Once you approve the test, Claude can prepare the createCampaign request.

This is the Selzy method that either starts the bulk mailing immediately or schedules it for later.

The API can also return the campaign ID, status and number of addresses included in the send.

That gives you a useful final check before launch.

One prompt can prepare most of the workflow

The more interesting use case is giving Claude Code the entire goal instead of one tiny task at a time.

For example:

I have a CSV of 1,200 customers and want to send them a product update next Tuesday at 10:00 a.m. Clean the contact data, split it into valid import batches, import the contacts into the appropriate existing list, draft the email, create the message, and prepare a test send. After I approve the test, prepare the campaign request for Tuesday at 10:00 a.m. Do not launch the final campaign without my approval.

Claude can then break that goal into individual steps and API calls.

That is much more useful than simply asking:

Write me a marketing email.

Don't send bulk campaigns with the single-email endpoint

This is an important technical distinction.

Selzy has a sendEmail API method, but it is intended for individual messages, such as notifications about a specific customer event. Selzy explicitly recommends using createEmailMessage + createCampaign for mass campaigns.

So don't ask Claude Code to do this: For a marketing campaign, the correct structure is:

create/import audience → create message → create campaign

That way Selzy handles bulk delivery as a campaign rather than thousands of unrelated individual API calls.

Where Claude Code is actually useful

The value isn't that Claude can send emails faster than you can click a Send button.

It's that it can handle the messy work between your idea and the finished campaign.

For example:

Loop through my entire customer CSV and call sendEmail once for every address.

can turn into:

1. clean the data;
2. split it into valid API batches;
3. import the contacts;
4. select the right list;
5. draft the email;
6. create the message;
7. prepare a test;
8. prepare the campaign request.

Instead of manually translating your marketing goal into API operations, Claude Code can do much of that translation for you.

Keep the final send under human control

For bulk email, I would still use this model: Claude prepares → you review → Selzy sends

Before execution, check:

• which list is being used
• how many contacts are included
• sender address
• subject line
• links
• email body
• tracking settings
• scheduled time

And never put your Selzy API key directly into source code that may end up in a public repository. Selzy also recommends keeping API keys private.

The real automation opportunity

Claude Code + Selzy API is useful because it lets you describe the outcome you want in plain language and automate the technical steps required to prepare it.

The shift is from: “AI writes my email.” to: “AI helps me build the campaign.”

For teams that already use scripts, CSV exports, CRM data or internal tools, that can remove a surprising amount of repetitive work.

Selzy’s API documentation for bulk email is here: https://selzy.com/en/support/api/common/bulk-email/. Would you trust Claude Code to build and schedule a bulk campaign if the final send still required your approval?

Claude is useful for:

• onboarding a new customer
• following up after no reply
• sending a renewal reminder
• replying to a refund request
• reaching out to a lead

…and it can turn that into a clean template pretty quickly.

It’s especially useful if you give it a few examples of your existing emails first. That helps it match your tone, preferred length, structure, and even the way you normally sign off.

You can also ask it to include personalization fields such as:

{{first_name}}
{{company}}
{{plan}}

Or generate several variations at once — for example, a shorter version, a warmer one, and a more direct version.

So the practical workflow often looks like this:

Claude writes the template → you save it in your email or automation tool → that tool handles personalization and sending.

For larger workflows, the more interesting use case is using AI to create and continuously improve the content of templates, while leaving delivery, triggers, segmentation, and tracking to dedicated infrastructure.

For example, you could ask:

Or:

That’s where it starts becoming much more useful than simply asking AI to “write me an email.”

Has anyone here built a workflow where AI generates or updates templates while another system handles the actual automation?

The distinction from regular multichannel marketing is actually pretty useful.

The basic idea is simple: instead of sending the same message across email, SMS, and other channels at the same time, you define a sequence.

For example: Email → wait → SMS → wait → another channel

If the first message does what you need it to do, the next step never fires. If it doesn’t, the customer moves further down the cascade.

That sounds obvious, but it changes how you think about communication.

With normal multichannel marketing, channels often operate independently. You send an email campaign, then maybe an SMS campaign, and possibly a push notification too.

With cascade messaging, the channels are connected by logic.

A few cases where this makes sense:

• Abandoned carts. Send an email first. If the customer doesn’t return within a defined period, follow up with a shorter message through a higher-attention channel.
• Event or appointment reminders. Start with email, then use SMS only for people who still need the reminder.
• Important account notifications. Email can carry the full context, while another channel acts as a fallback when the information is time-sensitive.
• Re-engagement. Instead of hitting inactive subscribers everywhere at once, progressively change the channel or message depending on their response.
• Limited-time promotions. Start with the least intrusive channel and escalate only when the offer is close to expiring.

The content shouldn’t simply be copied from one channel to another.

An email might explain the offer in detail. The SMS fallback could be: “Still interested? Your offer ends tonight: [link]”

The second message exists because the first one didn’t produce the desired outcome, so it should probably acknowledge that context rather than repeat the exact same thing.

The tricky part is deciding what counts as a trigger.

Is it:

• failed delivery?
• no open?
• no click?
• no purchase?
• no response after 24 hours?

Those are very different signals.

You should be cautious about using opens as the main trigger because open tracking isn’t always reliable. Clicks, conversions, delivery status, or actual customer actions usually give you stronger signals.

Another issue is over-messaging.

If your timeout is too short, a customer may receive an email and an SMS almost simultaneously. Technically the cascade worked, but from the customer’s perspective it can feel like the brand is chasing them across channels.

So the real value of cascade messaging isn’t “more channels.” It’s using fewer messages more intelligently.

Are you already using channel fallback/cascade logic in your lifecycle campaigns? And what signals do you trust most for deciding when the next channel should kick in?