AI reads, prioritizes, and summarizes your email into actionable digests. Read-only mode means zero risk — nothing is ever sent.
Executives and busy professionals spend over two hours daily processing email. Important messages get buried under newsletters, notifications, and low-priority threads. Action items are missed because they're scattered across dozens of conversations with no unified view of what needs attention.
MultiMail's AI agent processes your inbox in read_only mode, classifying emails by urgency and extracting action items. It generates prioritized daily digests so you see what matters first. Because the agent only reads — never sends — there is zero risk of accidental replies or data exposure.
Create a MultiMail mailbox connected to your email. The AI agent uses check_inbox and read_email to process incoming messages in real time.
The agent classifies each email by sender importance, urgency signals, and content type. VIP senders, deadline mentions, and decision requests are flagged as high priority.
The agent identifies action items, deadlines, and decision requests buried in email threads. These are extracted and organized into a structured task list.
A prioritized summary is compiled with the most important messages, pending action items, and threads requiring your attention — delivered as a structured briefing.
import requests
API = "https://api.multimail.dev/v1"
HEADERS = {"Authorization": "Bearer mm_live_xxx"}
"cm"># Fetch unread emails
inbox = requests.get(
f"{API}/mailboxes/my-mailbox-id/inbox",
headers=HEADERS,
params={"status": "unread", "limit": 50}
).json()
summaries = []
for msg in inbox["emails"]:
email = requests.get(
f"{API}/emails/{msg[&"cm">#039;id']}",
headers=HEADERS
).json()
summaries.append({
"from": email["from"],
"subject": email["subject"],
"preview": email["text_body"][:200],
"date": email["date"]
})
# Your AI processes summaries into a prioritized digest
print(f"Processing {len(summaries)} unread emails...")
for s in summaries:
print(f" [{s[&"cm">#039;date']}] {s['from']}: {s['subject']}")Pull unread emails and generate a prioritized summary digest.
import requests
API = "https://api.multimail.dev/v1"
HEADERS = {"Authorization": "Bearer mm_live_xxx"}
"cm"># Get a full conversation thread
thread = requests.get(
f"{API}/threads/{thread_id}",
headers=HEADERS
).json()
print(f"Thread: {thread[&"cm">#039;subject']}")
print(f"Messages: {len(thread[&"cm">#039;emails'])}")
# Read each message in the thread
for email in thread["emails"]:
full = requests.get(
f"{API}/emails/{email[&"cm">#039;id']}",
headers=HEADERS
).json()
# Your AI extracts action items from the body
print(f" From: {full[&"cm">#039;from']}")
print(f" Body preview: {full[&"cm">#039;text_body'][:150]}")Read full email threads and extract action items and deadlines.
"cm">// Check inbox for new emails
const inbox = await mcp.check_inbox({
mailbox_id: "my-mailbox-id",
status: "unread",
limit: 50
});
"cm">// Read and categorize each email
for (const msg of inbox.emails) {
const email = await mcp.read_email({
email_id: msg.id
});
"cm">// Tag by priority for digest organization
const priority = classifyPriority(email);
await mcp.tag_email({
email_id: email.id,
tags: [`priority-${priority}`, "processed"]
});
"cm">// Get full thread context for important emails
if (priority === "high") {
const thread = await mcp.get_thread({
thread_id: email.thread_id
});
console.log(`High priority thread: ${thread.subject}`);
}
}Use MCP tools to build a daily email digest with priorities and action items.
The agent only reads your email — it never sends, replies, or forwards. There is no possibility of accidental sends or data exposure through the AI agent.
Instead of scanning 50 emails to find 5 that matter, you get a structured digest with the most important items first and action items clearly extracted.
The agent reads entire conversation threads and summarizes the current state, so you don't need to re-read 20 messages to understand where things stand.
Executives who adopt email summarization report saving 2-3 hours per day that was previously spent triaging and reading low-priority messages.
Email infrastructure built for AI agents. Verifiable identity, graduated oversight, and a 38-tool MCP server. Formally verified in Lean 4.