Never Forget a Follow-Up Again

Tell your AI agent 'remind me about this next Tuesday' and get a contextual reminder delivered at the right time.


Why this matters

Important follow-ups slip through the cracks because there is no reliable way to schedule future reminders directly from email context. To-do lists get abandoned, calendar reminders lack the original context, and mental notes are forgotten by the next morning.


How MultiMail solves this

MultiMail's AI agent accepts natural language scheduling instructions and converts them into precisely timed reminder emails. Autonomous mode handles delivery automatically since reminders are self-directed and low-risk. Each reminder includes the original context so you know exactly what to act on.

1

Set a Reminder

Tell your AI agent what to remind you about and when. Natural language works: 'remind me to follow up with Chen about the proposal next Tuesday at 9am.'

2

AI Parses and Schedules

The agent converts natural language into a precise delivery time, handles timezone conversions, and composes a contextual reminder email.

3

Deliver on Schedule

Using send_email with autonomous oversight, the reminder arrives in your inbox at the specified time with full context about what action to take.

4

Include Original Context

If the reminder is tied to an email thread, the agent includes a summary of the original conversation so you have full context when the reminder fires.


Implementation

Send a Scheduled Reminder
python
import requests

API = "https://api.multimail.dev/v1"
HEADERS = {"Authorization": "Bearer mm_live_xxx"}

response = requests.post(
    f"{API}/send",
    headers=HEADERS,
    json={
        "from": "[email protected]",
        "to": ["[email protected]"],
        "subject": "Reminder: Follow up with Chen about partnership proposal",
        "text_body": (
            "You asked to be reminded:\n\n"
            "Follow up with Chen about the partnership proposal "
            "discussed on March 8.\n\n"
            "Context: Chen expressed interest in a co-marketing "
            "arrangement. You agreed to send a formal proposal "
            "by mid-March.\n\n"
            "Action: Draft and send the partnership proposal to "
            "[email protected]"
        ),
        "html_body": "<h3>Reminder</h3><p>Follow up with Chen...</p>"
    }
)
print(f"Reminder scheduled: {response.json()[&"cm">#039;id']}")

Create and send a reminder email for a future follow-up.

Create Context-Aware Reminders from Threads
python
import requests

API = "https://api.multimail.dev/v1"
HEADERS = {"Authorization": "Bearer mm_live_xxx"}

"cm"># Read the original thread for context
thread = requests.get(
    f"{API}/threads/{thread_id}",
    headers=HEADERS
).json()

"cm"># Extract key points from the conversation
latest = requests.get(
    f"{API}/emails/{thread[&"cm">#039;emails'][-1]['id']}",
    headers=HEADERS
).json()

# Schedule a follow-up reminder with thread context
response = requests.post(
    f"{API}/send",
    headers=HEADERS,
    json={
        "from": "[email protected]",
        "to": ["[email protected]"],
        "subject": f"Reminder: Follow up on &"cm">#039;{thread['subject']}'",
        "text_body": (
            f"Follow up on this thread with {latest[&"cm">#039;from']}:\n\n"
            f"Last message ({latest[&"cm">#039;date']}): {latest['text_body'][:200]}\n\n"
            f"Thread has {len(thread[&"cm">#039;emails'])} messages."
        )
    }
)

Set a reminder that includes context from an existing email thread.

MCP Tool: Quick Reminder Setup
typescript
"cm">// Read the email you want to follow up on
const email = await mcp.read_email({
  email_id: originalEmailId
});

"cm">// Get thread context
const thread = await mcp.get_thread({
  thread_id: email.thread_id
});

"cm">// Send a reminder to yourself
const reminder = await mcp.send_email({
  to: "[email protected]",
  subject: `Reminder: Follow up on '${email.subject}'`,
  text_body: `Follow up with ${email.from} about:\n${email.text_body.slice(0, 200)}`
});

"cm">// Tag for reminder tracking
await mcp.tag_email({
  email_id: reminder.id,
  tags: ["reminder", "follow-up", "march-2026"]
});

Use MCP tools to create reminders linked to email conversations.


What you get

Natural Language Scheduling

Say 'remind me next Tuesday' instead of navigating calendar apps. The AI handles timezone conversions and precise scheduling automatically.

Full Original Context

Reminders include summaries of the original conversation, so you know exactly what to follow up on without searching your inbox.

Instant Delivery with Autonomous Mode

Self-directed reminders are low-risk and benefit from autonomous delivery. No approval bottleneck between scheduling and delivery.

Inbox-Native Workflow

Reminders arrive in your inbox where you already manage tasks. No separate app to check — the reminder shows up where you'll see it.


Recommended oversight mode

Recommended
autonomous
Personal reminders are self-directed and low-risk. They're sent from you to you with no external recipients. Autonomous mode ensures reminders deliver at precisely the scheduled time without delays.

Common questions

Can I set reminders for other people?
Yes, but consider switching to gated_send mode for reminders sent to others so you can review the message before delivery. Self-reminders are safe for autonomous mode, but reminders to colleagues warrant a quick review.
How does the AI handle timezone conversions?
Your AI agent stores your timezone preference and converts natural language like 'tomorrow at 9am' into UTC for precise scheduling. It also handles cross-timezone references like 'Monday at 2pm ET' when you're in a different timezone.
Can I set recurring reminders?
Yes. Your AI agent can schedule recurring reminders — weekly follow-up checks, monthly report deadlines, quarterly review prep. Each recurrence includes updated context from the most recent communications.
What if I need to cancel a scheduled reminder?
Your AI agent tracks scheduled reminders and can cancel them before delivery. If a reminder is already in the MultiMail queue, you can use the cancel_message endpoint to prevent delivery.

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